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Course Title  Lead Instructors  ECTS Credits  Stream  Course Code 

Academic Communication: Preparatory English for Phd Exam (Term 12)
Efficient professional communication is the key to Academic success. The course is designed for PhD students who want to maximize their academic potential by boosting their ability to write research papers, present in front of multidisciplinary audiences, participate in scholarly discussions and engage in other forms of academic communication.
The main goal of the course is to enable PhD students to produce clear, correct, concise and coherent texts acceptable for the international professional community. The course is designed for a multidisciplinary audience. The course serves as a preparation for the qualification language exam, which is a prerequisite for the Thesis defense. 
Elizaveta Tikhomirova 
31.5 per term

DE030029  
Advanced Biostatistics in Agronomy  Laurent Gentzbittel  6  MA060400  
Advanced Molecular Biology Laboratory Practice
This course offers students the opportunity to work individually on laboratory projects assigned by the course instructor. During the term students are expected to have at least one entire working day in the lab, although additional days may be required. Final grades are determined by the students' final presentations, which describe their project/goals along with the results/progress accomplished. Participation in the course requires approval from the students' own advisors, as well as the instructors of the course

Konstantin Severinov  6  MA060046  
Advanced PLM techniques: Testing and Models Validation (Term 56)
This course is final course in PLM series and is devoted to the different types of testing and numerical models validation.
Students learn how to perform vibrational and modal testing in order to identify dynamic parameters of given structure. The modal testing is performed using laser scanning vibrometry. The results of modal and vibrational testing are used for finiteelement model validation and updating for accurate dynamics simulation. Also, so called HardwareintheLoop (HiL) testing is important part of the course. The idea of HiL is to upload the functional model of investigated system to realtime board and test it in combination with physical parts. During the course students perform a number of tests with the system that was designed and prototyped during courses Advanced PLM I and Advanced PLM II. Finally the results are used for system model validation. 
Ighor Uzhinsky 
63 per term

MA030254  
Advanced Quantum Mechanics (Term 12)  Mikhail Feigelman 
63 per term

DA060207  
Advanced Quantum Mechanics (Term 56)  Konstantin Tikhonov, Mikhail Feigelman 
63 per term

DA060207  
Applied Materials and Design
This course provides a broad base introduction into materials science and engineering of applied materials. The fundamental physical phenomena are considered that occur at different scales in the main classes of applied materials: metals, ceramics, polymers, natural materials, composites, and hybrids. The interrelation between thermodynamics, diffusion kinetics, and deformation behavior is explored. The concept of structure is introduced, and the nature of structural elements at the atomic, molecular, nano, micrometer and macroscopic scales is discussed: short and long range order in amorphous materials and crystals, defects, crystallites, grains and subgrains, precipitates, grain boundaries, interfaces, spherulites, etc. These are used to demonstrate the principal approaches to property control and evaluation in materials engineering and related technologies: chemical composition, synthesis, fabrication, heat treatment, plastic deformation, hybridization, and surface engineering.
Principles to control the properties are translated in terms of design performance. Ashby’s material selection algorithm for rational selection of materials for specific designs and applications will be taught here in comprehensive way – analysis of function, objectives and constraints, deducing of performance indices. All the concepts covered in lectures will be practiced by using CES EduPack a software to implement data intensive learning. The lectures will be supported with a number of laboratory practical lessons devoted to the development of practical skills in traditional materials science research flow – the visualization, characterization and modification of structure followed by the testing and analysis of properties. All the concepts covered in lectures will be the subject of exercises using open source software to implement data intensive learning. Individual projects (problems) will be formulated to introduce the CDIO approach in Applied Materials and Design. 
Alexander Korsunsky  3  MA030431  
Bayesian Methods of Machine Learning
The course addresses Bayesian methods for solving various machine learning and data analysis problems (classification, regression, dimension reduction, topic modeling, etc.).
The course starts with an overview of canonical machine learning (ML) applications and problems, learning scenarios, etc. and then introduces foundations of Bayesian approach to solve these problems. Bayesian approach allows one to take into account subject domain knowledge and/or user’s preferences through a prior distribution when constructing the model. Besides, it offers an efficient framework for model selection. We discuss which prior distributions types are usually used, limit properties of a posterior distribution, and provide some illustrations of the Bayesian approach. The practical applicability of Bayesian methods in the last 20 years has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, as well as posterior simulation methods based on the Markov chain Monte Carlo approach. As a result Bayesian methods have grown from a specialist niche to become mainstream. Therefore, we devoted a second part of the course to approximation tools, vitally important for Bayesian inference, and provide examples how to use Bayesian approaches to automatically select features, tune the regularization parameter in regression and classification, etc. The last part of the course is devoted to advanced Bayesian methods, namely, Gaussian Processes and deep Bayesian neural networks, which have become widespread in the last 58 years. We discuss deep Bayesian framework and then illustrate its applications through construction of deep variational autoencoders, approaches to variational dropout, Wasserstein Generative Adversarial Networks, deep Kalman filter, etc. Home assignments include solution of applied problems, development of modifications of Bayesian ML algorithms, and some theoretical exercises. 
Evgeny Burnaev  6  MA060129  
Bioinformatics
This course is aimed for the first year master students with no prior knowledge in bioinformatics. The main course idea is to get students from different backgrounds acquainted with basic tools and algorithms in bioinformatics, such as basic phylogenetic analysis, algorithms behind sequence alignments, protein structure analysis, gene and genome annotation, as well as main databases storing sequence, protein and epigenetics data.
The knowledge obtained during this course can be immediately utilized in the real biological and computational projects. 
Mikhail Gelfand  6  MA060307  
Biomedical Mass Spectrometry
This course introduces students to the first principles and methods of mass spectrometry with special emphasize on biological and medical applications. The course will cover wide range of mass spectrometry techniques used for ion generation, separation, detection and data processing and interpretation. The course will teach the theoretical fundamentals required for the design of instruments and methods for measuring mass spectra of biological samples. The course will cover mass spectrometry applications in OMICs technologies, mass spectrometry applications in biomarker discovery and tissue imaging.
After successful completion of this class, students will acquire the initial knowledge of the operational principles and design of different mass spectrometers, different methods of ionization of biological molecules of wide mass range, different methods of ion separation including magnetic sector, time of flight, RF and DC ion traps, as well as FTICR. Experimental and bioinformatics based methods of protein, peptides, lipids and metabolite molecule identification, different fragmentation methods for primary and secondary structure determination, methods of quantitative determination of proteins, lipids, metabolites and small molecule in physiological liquids 
Evgeny Nikolaev  6  MA060256  
Cancer Biology
The course is dedicated to basics of clinical and molecular cancer biology with emphasis on innovative drugs and technologies for cancer treatment and diagnostics.
The main themes to be discussed: What is cancer? Classification, staging, grading; The hallmarks of cancer; Mutations, oncogenes, tumor suppressors; Genomic instability; Epigenetics in cancer initiation and progression (miRNA, siRNA, lncRNA, methylation, histones modification, etc.); Cell cycle and growth and it’s deregulation in cancer; Tumor energy metabolism (the Warburg effect); Cell death and it’s deregulation in cancer (necrosis, apoptosis, autophagy); Cell differentiation and dedifferentiation in cancer, EMT, Metastasis; Cancer stem cells hypothesis; Tumor stroma and heterogeneity, neoangiogenesis; The “seed and soil hypothesis” – premetastatic niche; Extracellular vesicles for communication between cells; Cancer diagnostics, tumor markers; Liquid biopsy; Conventional treatment trajectories for patients; Biological factors in Cancer (inflammation, viruses, bacteria, microbiome); Target therapy, Immune checkpoint inhibitors; Emerging therapeutic modalities, CarT, dendritic cells, viruses; Invited medical oncologists will give talks on the usolved questions in the field. 
Vera Rybko  3  MA030088  
Classical Integrable Systems (Term 56)
Course description: A selfcontained introduction to the theory of soliton equations with an emphasis on their algebraicgeometrical integration theory. Topics include:
1. General features of the soliton systems. 2. Algebraicgeometrical integration theory. 3. Hamiltonian theory of soliton equations. 4. Perturbation theory of soliton equations and its applications to Topological Quantum 
Igor Krichever 
63 per term

MA060179  
Computational Imaging
In the computational era of everything, imaging has not become an exception. Computational algorithms allow both to extract valuable information from a scene and to improve the very sensor that forms the image. Today, computational and image processing enhancements became integrable parts of any digital imager, be it a miniature smartphone camera or a complex space telescope.
This crash course is designed as a prerequisite for those students who would like to venture into the field of Computer Vision. We will cover foundational mathematical equations that are involved in the image formation and in the geometric projection principles. The concept of Point Spread Function that distorts the object will be explained on particular examples and will be experimented with for the tasks of image reconstruction and denoising. Image processing will be covered with an emphasis on the Python libraries to be used in the rest of the imagingrelated courses on the DS/IST tracks (openCV and others). A basic DSLR photo camera will be considered as a model for understanding Fourier Imaging and Filtering methods in a laboratory exercise. Handson tutorials on how to select a camera and a lens for your machine vision application will be provided. The theory of color and stereo lightfield cameras will be covered using the models of commonplace Bayern RGB sensors; as well as stateofart spectral and multilens imagers. The course will consist of three theoretical lectures riffled by three graded inclass laboratory coding sessions on the subjects covered in the theoretical lectures. 100% attendance is mandatory. There will be a single inclass exam during the evaluation week and no homework. ATTENTION: Due to restricted access to laboratories during the pandemic, this course will be taught only to Ph.D. students in 2020. M.Sc. students may email the instructor for permission to enroll, provided students own a personal DSLR camera and are willing to perform experiments at home. 
Dmitry Dylov  3  MA030121  
Condensed Matter Spectroscopy and Physics of Nanostructures (Term 1B4)
This course presents a modern introduction to the field of optical phenomena in condensed matter and nanostructures. The first part of the course starts from the classical and quantum theory of electromagnetic response, and basics of the condensed matter spectroscopy. Then the major research directions in the modern condensed matter spectroscopy are considered, such as spectroscopy of graphene, topological materials, and twodimensional transition metal dichalcogenides. The second part of the course is focused on specific optical phenomena in semiconductors, heterostructures, nanostructures and interfaces, such as surface plasmons and polaritons, excitons, spinorbit coupling effects, Raman scattering and color centers.

Alexey Sokolik 
61.5 per term

Options  MA060313 
Critical Points of Functions (Term 12)
The theory of critical points of functions is of the main subjects of Singularity theory studying local geometry of singularities of differentiable maps as well as its relationship with global topological invariants of manifolds.
In the course we will discuss classification of critical points, its relationship with the ADEseries of simple Lie algebras and the corresponding reflection groups, their deformations and adjacencies. The study of a local topological structure of singularities will include description of Milnor fiber and vanishing cycles. We will discuss also application of the theory critical points to the study of caustics and wave fronts in geometric optics and classical mechanics, as well as enumeration of contact singularities in complex projective geometry. 
Maxim Kazarian 
63 per term

Options  MA060424 
Elliptic Operators in Topology of Manifolds (Term 12)
We plan to discuss two topics, which are central in topology of smooth manifolds, the hcobordism theorem and theory of characteristic classes. The hcobordism theorem proved by S. Smale in 1962 is the main (and almost the only) tool for proving that two smooth manifolds (of dimension greater than or equal to 5) are diffeomorphic. In particular, this theorem implies the highdimensional Poincare conjecture (for manifolds of dimensions 5 and higher). Characteristic classes, in particular, Pontryagin classes are very natural invariants of smooth manifolds. Computation of characteristic classes can help one to distinguish between nondiffeomorphic manifolds. We plan to finish the course with the theorem by J. Milnor on nontrivial smooth structures on the 7dimensional sphere. This theorem is based both on methods of Morse theory and theory of characteristic classes

63 per term

MA060258  
Energy Colloquium
The Energy Colloquium educates the audience in the presentday research and applications within the broader field of Energy Science and Technology. The Colloquium consists of a series of presentations by invited academic and industry speakers. The presentations target a nonspecialist audience.
All Master and Ph.D. students within the Energy Program are encouraged to attend the Energy Colloquium during the entire period of their studies. Students can earn 1 credit, if he/she participates in the Energy Colloquium over the course of any 2 terms of the academic year. Students who passed one round can make next (for credit) over the course of their subsequent studies. 
Alexei Buchachenko  1  Extra  MF010092 
Energy conversion systems optimal management and integration
This course will provide a graduate level overview of modern energy conversion systems ranging from state of the art commercial technologies, real world ones, generating electric/mechanic, heating and cooling power, as well as innovative solutions yet to be deployed massively, e.g. Flow Batteries, PowertoGas, Carbon Capture, Storage and Utilization (CCSU). During the course, the energy conversion units will be always studied from an integrated point of view considering their interaction with the surrounding energy infrastructures, electric, thermal/cooling and gas networks requirements, as well as the loads to be fulfilled. The whole course will look at the units from their optimal management point of view within such integrated framework, identifying the more suitable way to characterize their performance (e.g., constant, linear, nonlinear) consistently with the objectives, economic and/or environmental one. Such task is continuously increasing in complexity due to the uncontrollable Renewable Energy Sources increasing deployment, therefore units are facing technological developments, increasing their flexibility, and the energy infrastructures are increasing their level of mutual integration. Overall learning how to assess the adopted solutions is always more important, thus the core of the course is indeed represented by the identification of an integration problem, which will be assessed via the development of an optimization model to utilize assessing the validity of the investigated solution, both in economic terms as well as in environmental (primary energy consumption/CO2 emissions) on a research based teaching fashion.

Aldo Bischi  3  Options  MA030395 
English Toolkit (Term 1B2)
The goal of the English Toolkit course is to activate Academic English skills required for successful education at Skoltech.
The students will practice Academic vocabulary and grammar, as well as boost their reading, writing and speaking skills. The blended format includes a weekly online workload plus an offline group tutorial providing a flexible and individualised learning trajectory. Realtime feedback in online exercises will be complimented by tutor feedback for the writing and speaking assignments. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030001 
English. Candidate Examinations
This is a blended metacourse for the English Qualification Exam needed for the Russian PhD Degree. The Exam is designed as a multidisciplinary conference where the participants present results of their PhD research and follows the general principles of conference materials submission, peer review, resubmission, presentation, and discussion.
The goal of the Exam is Academic Communication, so the participants should demonstrate the ability to present their research results in front of a multidisciplinary audience and deliver the key ideas in good Academic English in terms of vocabulary, grammar and style. Preexam/ preconference activities, such as material submissions and peer reviews, last of three weeks and take place fully online. They include: Project proposal V1+ 2 Peer Reviews; a 2minute video annotation V1 + peer review; and a stack of presentation slides V1+ peer review. Version 2 of the Proposal, video annotation and the slides should be improved using the comments of the Instructor and the peers. Depending on the applicable regulations related to COVID19, on the Examination day students make their presentations and participate in the discussion in person or via an online platform in front of the Examination Committee and a group of peers. Failure to submit an assignment by the due date may result in the loss of the grade. The participants will practice a variety of academic skills: – Planning and designing a wellstructured and balanced presentation The grade is counted towards the PhD Qualification. 
Elizaveta Tikhomirova  3  DE030003  
Entrepreneurial Strategy
This course focuses on how scientists and technology entrepreneurs identify, design and implement strategies to sustain and enhance the success of the commercialization of their discoveries, examining issues central to the long and shortterm competitive position of the scientific and technological discoveries and developments they are willing to commercialize and transfer to society.
As a field, Strategy attempts to explain why and how some organizations outperform others in the marketplace, developing competitive advantages around technology, science or, overall knowhow, and sustaining these advantages over time while remaining competitive. The course provides a set of frameworks and analytical tools that enable scientists and technology entrepreneurs to understand and plan effective strategies for competing with their technologies in a range of industries. 
Alexander Chekanov  3  E&I  MC030023 
Essential Engineering Toolbox
The course is a seriеs of tutorials on essential tools that are extensively used throughout coursework and research in the Advanced Manufacturing Technologies program and generally in engineering practice. The tutorials involve handson exercises on a computer. After introduction to Latex, Python, Mathematica, Matlab and other basic tools, final topics in the course involve numerical computations of problems in solid and fluid mechanics with such widely used software as Abaqus, Ansys, and COMSOL. Students will be required to solve particular problems and write reports in Latex using the tool learned in the first tutorials.

Aslan Kasimov  3  MA030351  
Experimental Data Processing
The course introduces students to practically useful approaches of data processing for control and forecasting. The focus will be on identifying the hidden and implicit features and regularities of dynamical processes using experimental data. The course exposes data processing methods from multiple vantage points: standard data processing methods and their hidden capacity to solve difficult problems; statistical methods based on statespace models; methods of extracting the regularities of a process on the basis of identifying key parameters. The course addresses the problems in navigation, solar physics, geomagnetism, space weather and biomedical research and will be useful for broad range of interdisciplinary applications.

Tatiana Podladchikova  6  MA060238  
Finite Element Analysis
The course is intended to give basic knowledge and skills for finite element analysis method and procedures. The main topics of the course are introduction to FE theory and fundamentals, static stress analysis, structural stability, crack propagation analysis, extended finite element method (XFEM), explicit dynamic analysis, Eulerian analysis, particle methods, heat transfer and thermalstress analysis, submodeling. The both theory and practice with Abaqus software are given. Application of constitutive material models and equations of state are explained and demonstrated for typical problems.

Ivan Sergeichev  3  MA030355  
Foundations of Software Engineering
This course is intended to serve as an introduction into basics of everyday industrial software engineering. Oftentimes students seek to obtain proficiency in complicated subjects such as machine learning, algorithms, or computer vision, but lack basic literacy in software engineering and therefore have little practical skills required to carry out research or industrial projects. In this course, our goal is to bridge the gap between basic programming skills commonly taught during BSc programs and the industrialgrade engineering required by topnotch MSc, PhD, or R&D positions.
Topics include: As a project, the students will be required to work in teams to design, engineer, test, and deploy a real large software system using the principles described in this course. 
Alexey Artemov  3  MA030406  
Fracture Mechanics
Fracture mechanics is a large and always growing field since it focuses at one of the most significant problems in the industrialized world and a theoretical and practical basis for design against fracture is needed. Fracture mechanics deals essentially with the following questions: Given a structure or machine component with a preexisting crack or cracklike flaw what loads can the structure take as a function of the crack size, configuration and time? Given a load and environmental history how fast and in what directions will a crack grow in a structure? At what time or number of cycles of loading will the crack propagate catastrophically? What size crack can be allowed to exist in component and still operate it safely?
Fracture can and is being approached from many scales. For example at the atomic level, fracture can be viewed as the separation of atomic planes. At the scale of the microstructure of the material, the grains in a polycrystalline material, or the fibers in a composite, the fracture of the material around these features can be studied to determine the physical nature of failure. From the engineering point of view, the material is treated as a continuum and through the analysis of stress, strain and energy we seek to predict and control fracture. In this course, the emphasis is on continuum mechanics models for crack tip fields and energy flows. A brief discussion of computational fracture, fracture toughness testing and fracture criteria will be given. This course is designed for students who want to begin to understand, apply and contribute to this important field. 
Sergey Abaimov  3  MA030248  
Fundamentals of Optics of Nanoscale Systems (Term 1B4)
The course focuses on the general concepts and experimental developments in the rapidly evolving field of the modern physics of nanosized systems. It covers a broad spectrum of optics on the nanometer scale, ranging from fundamental nanoscience to nanotechnology applications. Topics covered include: foundations of lightmatter interaction at nanoscale, concepts of nearfield and quantum confinement, nanoplasmonics, optical emission of pointed nanoparticles (fluorescent molecules, quantum dots, plasmonic nanoparticles et al). Various experimental methods that used in nanooptics and nanoscience, including nearfield and farfield optical microscopy of subdiffraction spatial resolution, are presented. Nanophotonic devices, photonic crystals, spasers, singlephoton sources, nanosensors are discussed. Seminars assume the discussion of papers presenting a physical basis for nanoscale optical phenomena, as well as the papers describing the last achievements in the area.

Yuri Vainer 
61.5 per term

Options  MA060437 
Geometric Representation Theory (Term 12)
Geometric representation theory applies algebraic geometry to the problems of
representation theory. Some of the most famous problems of representation theory were solved on this way during the last 40 years. The list includes the Langlands reciprocity for the general linear groups over the functional fields, the LanglandsShelstad fundamental Lemma, the proof of the KazhdanLusztig conjectures; the computation of the characters of the finite groups of Lie type. We will study representations of the affine Hecke algebras using the geometry of affine Grassmannians (Satake isomorphism) and Steinberg varieties of triples (DeligneLanglands conjecture). This is a course for master students knowing the basics of algebraic geometry, sheaf theory, homology and Ktheory. 
Mikhail Finkelberg 
63 per term

MA060271  
Hack Lab: Laboratory for Ideas  Zeljko Tekic  6  E&I  MC060024 
Heterogeneous Volume Modeling and Digital Fabrication
The course covers methods and techniques of digital modeling of volumetric point sets with attributes presenting pointwise properties such as material fractions, color, and other volumetric object properties. Modelled objects are characterized by complex volumetric geometry, multiscale microstructures and volumetric multimaterial density distribution. Stress will be made on using continuous and discrete scalar fields for modelling both geometry and attributes. Associated methods of multimaterial digital fabrication will be outlined.

Alexander Pasko  3  MA030299  
Introduction to Advanced Manufacturing Technologies
The course provides an introduction to the field of Advanced Manufacturing and Digital Engineering Technologies and focuses on main research and educational thrusts of the Center for Design, Manufacturing and Materials (https://https://crei.skoltech.ru/cdmm): Advanced Manufacturing Technologies, Digital Engineering Technologies, Science of Advanced Manufacturing, and Computational Engineering.
The first thrust is focused on advanced technologies such as Advanced Manufacturing of Composite Materials, Additive Technologies, Thermal Spray Coatings, and Materials Selection in Design. The second thrust is focused on digital engineering technologies related to simulationdriven product development, model based systems engineering, digital manufacturing, product lifecycle management, and geometric modeling in ComputerAided Design. The last two consist of fundamental disciplines required to understand the mechanics and physics of advance manufacturing processes, to develop mathematical and computational models of these processes to predict and improve the properties of the materials, structures, and engineering systems, as well as to develop digital twins of manufacturing processes and their individual components, what is commonly referred to as simulationbased engineering science. Professors and research scientists from the Center for Design, Manufacturing and Materials will introduce students to the Center laboratories, to ongoing research activities, and propose possible projects for Master's thesis research. This course will help students to select a specialization and future research advisors. 
Aslan Kasimov  3  MA030296  
Introduction to Artificial Intelligence
This is an introductory course which overviews general aspects of Artificial Intelligence such as main applications, ethics, current trends and challenges etc.
The course is aimed for 1st year MSc students who would like to become familiar with AI. Although the course does not go deeply into technical details of AI (which will be fought later on by other courses in the Data Science program), it will be also of interest to those who have experience in AI but would like to understand the general role the new AI technologies play in the modern society. During the course several topics will be discussed: 
Maxim Fedorov  3  MA030358  
Introduction to Data Science
The course gives an introduction to the main topics of modern data analysis such as classification, regression, clustering, dimensionality reduction, reinforcement and sequence learning, scalable algorithms. Each topic is accompanied by a survey of key machine learning algorithms solving the problem and is illustrated with a set of realworld examples. The primary objective of the course is giving a broad overview of major machine learning techniques. Particular attention is paid to the modern data analysis libraries which allow solving efficiently the problems mentioned above.

Mikhail Belyaev, Maxim Panov 
3  MA030111  
Introduction to IoT
In the last decade the Internet of Things (IoT) paradigm has slowly but steadily and increasingly permeated what researchers and engineers study and build. The term “Internet of Things” doesn’t have a single definition and people today often use it to interchangeably refer to Wireless Sensor Network (WSN), MachinetoMachine (M2M), Web of Things (WoT) and other concepts. The focus of this course is to learn about these technologies that will be extending the Internet as we know it and use it today, to interconnect not only people and computers but also sensors and associated objects. The course will be divided into two strongly coupled parts. The first part of the course covers the IoT ‘pillar’ technologies, i.e. embedded systems, wireless sensor networks, semantic technologies, and theory behind them while the second part will have a special focus on IoT development, i.e. IoT apps, open platforms, sensors and actuators, software/middleware. Apart from covering the theory behind the IoT and “how to connect things to the Internet”, the course will therefore also engage the students to demonstrate the feasibility of simple IoT real applications and will challenge them to improve their applications through the use of cognitive technologies and cloud computing.

Andrey Somov  3  MA030233  
Introduction to Petroleum Engineering
The course is an introduction to Petroleum Engineering and gives an overview of Petroleum Engineering and its various components and their internal connection.
The course will address the story of oil from its origin to the end user. The objective is to provide an overview of the fundamental operations in exploration, drilling, production, processing, transportation, and refining of oil and gas. As additional topics it is planned to consider Permafrost Engineering and Flow Asuurance, which are actual for Russian Oil&Gas Industry. Within the framework of the course it is planned to invite speakers form industry. 
Dimitri Pissarenko  3  MA030064  
Introduction to Programming for Biologists
Science is constantly changing. The more and more complicated analyses are needed for publication, not only for a theoretical study but also for experimental research. In the light of ongoing development of new highthroughput experimental techniques, the skill of data processing and analysis becomes inevitable for any researcher.
One of the most used tools to process data and make publicationquality plots is Python programming language. Python is simple, powerful, and extremely popular. Among programming languages, Python is the closest to natural languages making it easy to begin with. In the course “Introduction to Programming for Biologists” I will provide basic knowledge of Python in a simple form suitable for understanding by all students, especially by completely unfamiliar with programming. With many exercises, students will inevitably master their programming skills to the level appropriate for processing their own data and making basictomedium analyses. 
Dmitry Ivankov  3  MA030372  
Introduction to Quantum Groups (Term 12)
Quantum groups were introduced in the mid80's and very quickly became one of the most important topics in mathematics and mathematical physics. They are still actively studied, and their knowledge is necessary for work in many areas.
The purpose of the course is an introduction to quantum groups. The content will be based on classic works of the 80's and early 90's, we will not get to the latest results. Initial knowledge about quantum groups is not assumed, but acquaintance with Lie algebras and Groups, Poisson brackets, and the first notions of category theory is assumed. 
Mikhail Bershtein 
63 per term

Options  MA060426 
Introduction to Wireless Communication
The course gives an introduction to the most important aspects of modern wireless communication systems. The course covers basic wireless communications processes like signal transmission, propagation, detection, and demodulation. Students will get familiar with some informationtheoretic concepts like channel capacity and errorcorrecting codes. This introduction also highlights multiple antenna techniques and modern cellular system architectures, including the InternetofThings concepts. The practical part of the course includes a series of labs (MATLAB) that allow discovering basic principles as well as advanced methods for wireless communication systems analysis.

Kirill Andreev  3  MA030409  
Introduction to the Quantum Field Theory (Term 12)
Introduction to basic notions of gauge theory: gauge invariance, SU(N) Lie algerbras and their representations, Yang Mills Largangian and its quantization, FaddeevPopov method, ghosts and unitarity, diagram technique, basics on perturbation theory, analysis of simplest Feynman diagramms, beta function in nonabelian YangMills theory, renormalization group, asymptotic freedom, Higgs mechanism, basic notions of QCD and electroweak theory. Depending on progress: some advanced topics: anomalies, instantons.

Yaroslav Pugai 
63 per term

MA060273  
Introduction to the Theory of Disordered Systems (Term 12)
This course is mainly dealing with the quantum electronic properties of disordered materials. I start with a review of different types of disorder and general methods of their theoretical treatment. Then I give a detailed discussion of the two popular models of quenched disorder, widely used for description of quantum solid state systems: Anderson model and Lifshits model. I discuss the properties of the disordered systems in the insulating phase: the density of states, the tails in the optical absorption ( with the optimal fluctuation method) and different versions of hopping conductivity: the nearest neighbour hopping and the Mott's variable range hopping. I also take into account the longrange Coulomb correlations and derive the Coulomb gap in the density of states and the EfrosShklovskii law for the conductivity.
As to the vicinity of the metalinsulator transition, I give a qualitative discussion of the mechanism behind the transition, as well as the most powerful tools for probing the properties of the system near the transition: analysis of inverse participation ratios and the concept of multifractality of the wavefunctions. In the metallic phase I discuss the weak localization corrections, including magnetoresistance, inelastic phasebreaking mechanisms and interactioninduced anomalies in the density of states near the Fermi surface. At the end of the course I give a brief introduction to mesoscopics, including the Landauer formalism and quantization of the ballistic conductance. 
Alexey Ioselevich 
63 per term

MA060274  
Laser Spectroscopy (Term 1B4)
Spectroscopy is a science of studies of the quantum objects using the light. Before the laser era, its methods were limited to the spectroscopies of emission, absorption, and Raman scattering. The subject of the present course is not so much an improving, using the lasers, performance of the classical approaches (although this also is mentioned) but rather learning the new (more than a dozen) methods that have become possible only due to the appearance of the lasers. The course provides knowledge of the fundamental processes in spectroscopy as well as the methods allowing one to solve the problems that require (i) ultrahigh sensitivity, (ii) ultrahigh selectivity, (iii) ultrahigh spectral resolution, and (iv) ultrahigh temporal resolution. As an elective, the effects of quantum interference are considered such as coherent population trapping, the Autler–Townes effect, electromagnetically induced transparency, lasing without inversion, and more.

Alexander Makarov, Alexey Melnikov 
61.5 per term

Options  MA060212 
Leadership for Innovators
Succesful innovators are distinguished not only by their scientific excellence as well as end user vision, but also by superior leadership skills. Scientists dream about being honored and awarded by fans on the merits of their science alone, but unfortunately it never works this way. Innovation is impossible without leading, cooperating, negotiating, and keeping resilience from the constant stress. This course presents the comprehensive skillset of leadership that includes theory and practice of:
– leadership & teamwork – selfawareness and goal setting – stress management and selfpresentation – empathy and 360 feedback – influence & negotiations The recurring topic of the class is that all these beneficial skills are fuzzy and overrated unless they are taken together in the globally accepted framework of "Emotional Intelligence" (EQ). The class is built as highly interactive action that starts with Q&A on a particular component of the EQ toolkit and then culminates in the intensive group and personal exercises. Unlike your favorite hard skill classes, this course is light on homework, but hard on class participation. Student should be ready to attend at all costs or face course failure. If you miss the class, you steal learning experience not only from yourself, but also from the entire group, hence consequences will be serious. Please note that this class is 80% similar to the ISP combo of "Hardcore EQ" and "Negotiation games" so you may optimize your learning schedule. 
Maxim Kiselev  3  E&I  MC030011 
Master Your Thesis in English (Term 56)
The key to efficient professional communication is the ability to convey ideas clearly, coherently and correctly both orally and in writing.
The Course offers concise and practical guidelines for writing and defending a Master Thesis at Skoltech. The course focuses on the main parts of the Thesis in terms of structure, vocabulary and grammar, and their transformations for a presentation with slides. Students will develop a conscious approach to own writing and presentations through thorough analyses of the best authentic examples combined with intensive writing and editing practice. The ‘processforproduct’ approach teaches the students to write – use (peer) reviewer’s advice – revise/edit – repeat, and creates linguistic awareness needed to avoid the typical pitfalls. The Course is offered in two modules which gradually build on the necessary writing and presentation skills. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030003 
Master Your Thesis in English 1 (Term 5B6)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030003ls 
Mathematical Methods in Engineering and Applied Science (Term 12)
The course introduces students to mathematical methods widely used in modern engineering and applied sciences. It consists of three main parts: 1) Methods of Applied Linear Algebra (solving linear systems, LU, QR, SVD, and other factorizations, Principal Component Analysis, iterative methods, FFT, least squares, pseudoinverse, etc.); 2) Statistical Methods and Data Analysis (mean, variance, probability; moments, covariance, Gaussian processes, Markov chains; regression, gradient descent; neural networks, machine learning); and 3) Applied Differential Equations (linear and nonlinear ordinary differential equations, stability and bifurcations of solutions, linear and nonlinear partial differential equations, hyperbolicity, characteristics, dispersion, reactiondiffusion phenomena, pattern formation).
The course is introductory by nature, covering a wide range of topics and methods of modern interest in applications. Its theoretical content is informal in style and most of the concepts will be illustrated with problems from engineering, physics, chemistry, and biology using numerical computations in Matlab and Python. The three parts of the course are aimed at: part 1 – using the right language that is crucial for understanding many computational techniques used in engineering; part 2 – learning important tools of analysis of results obtained either by computation or in experiments; and part 3 – learning the nature of key mathematical models that form the foundation of engineering and applied sciences. 
Aslan Kasimov 
63 per term

MA060352  
Mathematical Methods of Science (Term 12) The course is addressed to undergraduates of the first year and contains applications of various mathematical methods for solving problems of mathematical physics. The course assumes a minor familiarity with basic notions of classical mechanics and field theory on the example of solving specific problems. The main purpose of the course is to encourage undergraduates to independent research work. For this reason, the main element of the course is an independent solution to the problem, requiring the study of additional material. In the endpoint the students are assumed to acquire the use of Green functions, distributions, Laplace and Fourier transforms, asymptotic evaluations in mathematical physics 
Sergei Khoroshkin 
63 per term

Options  MA060317 
Mathematics for Engineers
The aim of this is to recap the basic topics that you are expected to get at bachelor level. If you do not feel confident with basic matrix manipulations, integration and differentiation – you should definitely take this course; fluency in these is a must for an educated engineer. At the first day of studies you’ll take the preliminary exam to make final decision regarding taking this course.

Elena Gryazina  3  MA030282  
Matrix and Tensor Factorizations
Machine learning and data mining algorithms are becoming increasingly important in analyzing large volume, multirelational and multi–modal datasets, which are often conveniently represented as block matrices and/or multiway arrays or tensors. It is therefore timely and valuable to teach lowrank matrix tensor factorizations and tensor networks as emerging tools for largescale data analysis and data mining. We provide the mathematical and graphical representations and interpretation of matrix and tensor factorizations with the main focus on Higher Order Singular Value Decomposition (HO_SVD), Multilinear Principal Component Analysis (PCA), Robust PCA, Independent Component Analysis ( ICA), Nonnegative Matrix Factorization (NMF), Canonical Polyadic Decomposition PARAFAC (CP decomposition) , the Tucker and Tensor Train (TT), Tensor Chain and Hierarchical Tucker decompositions and their extensions or generalizations.
To make the material selfcontained, we also address the concept of tensorization, which allows for the creation of very highorder tensors from lowerorder structured datasets represented by vectors or matrices. Then, in order to combat the curse of dimensionality and possibly obtain linear or even sublinear complexity of storage and computation, we address supercompression of tensor data through lowrank tensor decompositions. We also explain the concepts of lowrank matrix/tensor approximations and the associated machine learning algorithms. We then elucidate how these concepts can be used to convert otherwise intractable hugescale optimization problems into a set of much smaller linked and/or distributed subproblems of affordable size and complexity. In doing so, we highlight the ability of tensor decompositions to account for the couplings between the multiple variables, and for multimodal, incomplete and noisy data. 
Anh Huy Phan, Andrzej Cichocki 
3  MA030303  
Molecular Biology
Molecular biology course is based on learning the principles of replication, recombination, DNA repair. Additionally, replication strategies of phages and viruses will be discussed. Mitosis and meiosis will be described in a context of DNA biosynthesis. Also, the principles of RNA biosynthesis, i.e. transcription and processing, as well as protein biosynthesis, i.e. translation, maturation and transport will be described.
The goal of the course is obtaining a comprehensive knowledge on the structure of DNA and processes of DNA replication, recombination and repair in bacteria and eukaryotes, as well as on replication of phages and viruses. To obtain a detailed knowledge on the processes of transcription, in bacteria and eukaryotes, on the regulation of transcription in bacteria and eukaryotes, on examples of complex networks of transcriptional regulation in bacteria and eukaryotes, on maturation of RNA in eukaryotes, on protein biosynthesis in bacteria and eukaryotes, on the transport of protein in bacteria and eukaryotes. Students activities include: 
Petr Sergiev  6  MA060034  
Molecular Spectroscopy (Term 1B2)
The spectra of molecules provide unique information about the structure and properties of substances that can be used to accurately determine the composition of the atmospheres of planets and interstellar medium, to analyze the causes of global warming and to estimate the thickness of the Earth’s ozone layer, to detect impurities in pure gases and liquids, to detect toxic and explosive substances, to study the biological activity of molecules, etc. The course examines the physical phenomena leading to the occurrence of absorption, emission or scattering spectra, the structure of these spectra due to rotations, vibrations and changes in the electronic state of molecules, as well as questions of the experiment, the various types of spectrometers, data processing methods.

Leonid Surin 
31.5 per term

Options  MA030209 
Nanooptics
Nanooptics aims at the understanding of optical phenomena on the nanometer scale, i.e. near or beyond the diffraction limit of light. Typically, elements of nanooptics are scattered across the disciplines. Nanooptics is built on the foundation of optics, quantum optics, and spectroscopy. In the presence of an inhomogeneity in space the Rayleigh limit for the confinement of light is no longer strictly valid. In principle infinite confinement of light becomes possible, at least theoretically.
The course will cover basic theoretical concepts, multiphoton microscopy, interaction of light with nanoscale systems, optical interaction between nanosystems, and resonance phenomena, namely localized surface plasmons, surface plasmon polaritons, and microresonators. 
Vladimir Drachev  3  MA030153  
Neuroimaging and Machine Learning for Biomedicine
Nowadays Computational Neuroscience and Neuroimaging are fastgrowing areas mostly due to new methods of acquiring, storing and processing of experimental data. Application of AI systems in clinics (for example, creating medical decision support systems) and in adjacent areas (education, pedagogics, etc.) includes processing of Neuroimaging data acquired from different devices (modern multichannel “dense” EEG systems, highfield MRscanners, multichannel fNIRS systems, which allow precisely and noninvasively record brain activity with good spatial and temporal resolution), automation of these data analysis, and new knowledge extraction from it. The majority of relevant tasks include: classification tasks for diagnostics and prognosis, finding clinically (biophysically) significant patterns, highlighting areas of interest and others.
Neuroimaging data has several distinctive properties: it is multimodal, highdimensional and usually very noisy. An effective analysis of these data requires understanding of the biophysical processes in the organism and the processes occurring in the scanning equipment, which are both reflected by neuroimaging data, as well as the use of a number of mathematical models that adequately describe these processes. The aims of the course are: • to explain basic ideas and results in tasks and approaches for the neuroimaging data preprocessing based on biophysical principles and processes in scanning equipment, • to give a review of various mathematical models describing the neuroimaging data reflecting their specific properties, • to teach the student how to use the conventional or modified Data Analysis and Machine Learning techniques for extracting meaningful biomarkers from the data and solving fundamental neuroscience problems as well the applied biomedical tasks. 
Maxim Sharaev  3  MA030421  
Parallel Computing in Mathematical Modeling and DataIntensive Applications (Term 56)
This interdisciplinary course:
— makes the students familiar with main scientific and engineering applications of modern supercomputers, — explains numerical methods behind the applications and their implementation — discusses efficiency of the common algorithms on modern supercomputer architectures — extends students background in modern processors and supercomputer architectures The applications includes computations fluid dynamics with finite difference and finite volume methods, Lattice Boltzmann and cellular automata, finite elements modeling, molecular simulations, plasma, quantum chemistry, distributed deep learning on multiple computing devices, processing big volumes of data (e.g. large graphs) on distributed systems. Each topic includes a lecture by a lead instructors, invited highprofile guest lecturers and students. Each lecture is devoted to a particular application. Students will form teams to work on projects in one of the application areas and then share their experience with the fellow students at seminar sessions and a final project presentation at the conclusion of the course. 
Sergey Rykovanov, Alexey Vishnyakov 
63 per term

MA060411  
Pedagogical Experience  Dmitry Artamonov  3  DE030005  
Phase Transitions: Introduction to Statistical Physics and Percolation (Term 12)
This is a course on rigorous results in statistical mechanics, random fields, and percolation theory. We start with percolation, which is the simplest system, exhibiting singular behavior, and undergoing phase transitions. We then go to more realistic models of interacting particles, like the Ising model and XYmodel, and study phase transitions, occurring there.
The topics will include: Percolation models, infinite clusters. Crossing probabilities for rectangles Critical percolation The RussoSeymourWelsh theory Cardy’s formula in Carleson form and the Smirnov theorem. Gibbs distribution DobrushinLanfordRuelle equation Ising model Spontaneous symmetry breaking at low temperatures O(N)symmetric models The Mermin–Wagner Theorem The Berezinskii–Kosterlitz–Thouless transition Reflection Positivity and the chessboard estimates Infrared bounds 
Semen Shlosman 
63 per term

MA060427  
Quantum Mechanics
The course will review the basic concepts of quantum mechanics. It is intended both for those who studied quantum mechanics previously and for those who did not. The purpose of the course is not only to introduce the main principles of quantum mechanics but to familiarize with them through active problem solving, which is the only practical way to study quantum mechanics. The course will cover the main topics such as onedimensional motion, perturbation theory, scattering theory, approximate methods in quantum mechanics, density matrix formalism.

Mikhail Skvortsov  3  MA030177  
Quantum Mechanics (Term 12)
Advanced course in quantum mechanics, in which the basic principles
quantum theory is supplemented and applied to the study of specific physical systems. Modern methods of research of quantum systems are proposed – the construction of integrable potentials, the integral along trajectories, and the concepts of density matrix and effective action are introduced. The course involves a transition to the consideration of free field theories, their canonical quantization, and discussion of differences quantum mechanics from quantum field theory. The purpose of the course is to consolidate the basic principles and methods of quantum theory, study the transition from quantum mechanics to quantum field theory. The course introduces the basic concepts necessary for studying the courses of the program "Mathematical physics". The course is designed as a solution to specific problems in quantum theory (see the course content). The course involves significant independent work on solving problems. I would like the results of the course to coincide with the goals. 
Vladimir Losyakov 
63 per term

MA060428  
Quantum Theory of Radiation and Quantum Optics (Term 1B4)
The main goal of the course is to study by students basic physical principles, main quantum electrodynamical (QED) phenomena and mathematical apparatus of quantum electrodynamics and quantum optics. Students must know theory and experimental data on interaction of radiatiation with matter. Particularly will be discussed: quantum theory of electromagnetic field, problem of phase in QED, coherent and squeezed states, relativistic quantum theory of electrons and positrons, Klein paradox, diagram technique,
divergences and renormalization of mass and charge of electron, Lamb shift, cavity quantum electrodynamics (including last achievements), dynamical Casimir effect, basics of united theory of electromagnetic and weak interactions etc. 
Yuri Lozovik 
61.5 per term

Options  MA060314 
RNA Biology
This course is devoted to the knowledge on the structures of RNA and RNAprotein complexes as well as their functioning in cells. The aim of this course is to provide an explanation of fundamental mechanisms such as translation, splicing and gene expression regulation based on the structural viewpoint. Thus the role of RNA in the maintenance of cell identity and cell metabolism will be defined. By focusing on modern techniques for RNA and RNAprotein structure and RNA modifications analysis, students will get aquainted with the approaches to study RNA input into cellular processes in vitro and in vivo.
The students will apply obtained knowledge and skills in presentations and a written exam. An examination commission, consisting of CTB faculty and of invited members, will conduct final evaluation of the overall product design completeness, quality of the results achieved, and of the presentations delivered. 
Timofei Zatsepin  3  MA030081  
Reinforcement Learning
Reinforcement learning (RL) is a vanguard method of machine learning aimed at dynamical applications, ranging from video games to autonomous cars, robots, drones etc. Composed of an agent and an environment, it is meant to resemble the behavior of living beings somewhat. RL is truly an interdisciplinary subject that can be studied from different kinds of perspectives – machine learning, control theory, dynamical system theory, pure math (e.g. approximation theory) etc.
In this course, we dive into RL with the goal of understanding and trying out the key principles thereof. We will study how agents interact with the environment and optimize their actions to improve rewards. Speaking of examples, imagine a video game speed run. An agent, the protagonist, interacts with the game environment and wants to beat the game as fast as possible, by dynamically adjusting his or her controls while learning onthefly. At first, we will make a soft, less formal, introduction into RL and then proceed to its fundamentals – dynamical systems, agents, actors, critics etc. Secondly, we will address how RL arises from a general setting of optimal control followed by a menu of concrete methods. There is a huge amount of those and you will have the opportunity to pick one and try it our yourself. Last part of the course discusses some advanced topics of RL – convergence issues, relation to various control methods, safety. The course comprises of 6 lectures, 6 seminars, 3 home works, 2 labs and a final project. The PhD students will have one extra home work assignment. 
Pavel Osinenko  3  MA030422  
Representations of Classical Groups and Related Topics (Term 12)
The course is focused on fundamental results of the representation theory of classical matrix groups, which find numerous applications in various domains of mathematics. Particular attention will be paid to links with algebraic combinatorics.
Tentative program: – Characters of classical groups (general linear, orthogonal, and symplectic). 
Grigori Olshanski 
31.5 per term

MA030423  
Research (Term 58)  Mikhail Skvortsov 
61.5 per term

MA060432  
Research Methodology: Space Center Seminar (Term 14)
The seminar will cover current topics in the space domain: latest news, discoveries. Also planned that all PhD students and some Master students will present their research. External lecturers will be invited regularly to focus on the main applications of space technologies: science, telecommunication, navigation and remote sensing. Aspects of space technologies will also be discussed: structures, software, attitude determination and control systems, on board computers, communication system power supply systems and others. The seminar will be offered in English.

Anton Ivanov 
30.75 per term

DA030102es  
Research seminar "Modern Problems of Mathematical Physics" (Term 14)
Course "Modern problems of mathematical physics" is a student seminar, so participants are expected to give talks based on the modern research papers. Current topic of the seminar can vary from time to time: now it is devoted to the study of N=2 supersymmetric gauge theory and its links with random matrix models, ABJM theory, localization, complex curves, and integrable systems. Other topics that were already covered, or can be covered in the future, are: classical integrable equations, complex curves and their thetafunctions, quantum integrable models (quantummechanical and fieldtheoretical), models of statistical physics.

Pavlo Gavrylenko 
61.5 per term

DA060268  
Research seminar "Modern Problems of Theoretical Physics" (Term 14)
Research seminar "Modern Problems of Theoretical Physics" is supposed to teach students to read, understand and represent to the audience recent advances in theoretical physics. Each student is supposed 1) to choose one of recent research papers from the list composed by the instructor in the beginning of each term, 2) read it carefully, 3) present the major results of the paper to his/her colleagues during the seminar talk, 4) answer the questions from the audience about the content of the paper. The papers in the list are selected, normally, from the condensed matter theory and related fields, like: physics quantum computing, statistical physics, etc. The papers to the list are usually chosen from most competitive physics journals, like Nature Physics, Science, Physical Review Letters, Physical Review X and others.

Mikhail Feigelman, Konstantin Tikhonov 
61.5 per term

DA060319  
Research seminar "Supersymmetric Gauge Theories and Integrable Systems" (Term 12)
The course will be devoted to the study of N=2 supersymmetric gauge theories and related topics. It turns out that comparing to the N=1 theories, N=2 allows to compute much more quantities. In particular, lowenergy effective action can be described in terms of single function, prepotential. SeibergWitten solution of the N=2 theory gives explicit description of the prepotential in terms of periods of some meromorphic differentials on algebraic curves. It turns out that this description is deeply related to classical integrable systems.
During the course we will learn basics of the N=2 theories, classical solutions, holomorhy arguments, and so on, study SeibergWitten exact solution, and then its underlying integrable systems. We are also going to learn some modern developments of this topic, like Nekrasov instanton computations and AGT relation. 
Pavlo Gavrylenko, Andrey Marshakov 
63 per term

DA060382  
Scientific Computing
This is an introductory course to Scientific Computing with a focus on mathematical and algorithmic aspects of HighPerformance Computing (HPC) techniques and their areas of applications. The course has also a practical component, consisting of learning basic principles of HPC and applying the acquired knowledge and skills to solving industryrelevant problems in oil & gas, electrochemical energy storage, aerospace, food and pharmaceutics.
The practical aspects of use of a variety of computational techniques for solving scientific and engineering tasks will be taught during practical demonstrations and they will be integrated as much as possible with the corresponding theoretical materials given during the lectures. During the practical demonstrations the students will get access to the parallel cluster in Skoltech. All topics in the course will be covered at an advanced introductory level, with the goal that after passing the course the students will learn enough to start using scientific computing and HPC methods in their everyday research work. Once the students reached that level, they will learn more details and more advanced subjects in other courses in the overall Computational Science & Engineering program. Students should be comfortable with undergraduate mathematics, particularly with basics of calculus, linear algebra and probability theory. Some preliminary knowledge of Unixlike operative systems is a plus. Many of the examples used in lectures and assignments will require this background. Although the course will overview most popular pieces of commercial software used in HPC, all of the software used for practical tasks in this course is open source and freely available. 
Nikolay Koshev, Dmitry Yarotsky 
6  MA060113  
Soft Condensed Matter
The course introduces students to the physical, engineering and modeling aspects of soft systems, that is the systems that can be structurally altered by forces comparable to thermal fluctuations in magnitude. Soft matter is abundant in industrial processes (in particular, oil recovery and processing, detergents, adhesives, etc) and in biosystems, including the very human body. Specific topics will include interactions in emulsions and dispersions, stability of thin films and colloids, rheology, and aggregation dynamics. The emulsion block is followed by the behavior of amphiphiles, selfassembly, liquid crystals and colloids stabilization. Soft polymeric structures are next, and the final part will feature either lipid layers and membrane proteins (provided the interest or foams). The course program may be slightly altered depending on the students taking (some topics may be strengthened and some omitted if there is no interest in them).
The course will be useful to all students willing to improve their understanding of natural (e.g. mineral oil) and manmade colloids and polymers. The course will also provide a handson experience in numerical methods of soft matter modeling via theoretical statistical approaches and mesoscale simulations, gained via homeworks and term projects. Term project will involve both physicsdriven and datadriven approaches, as the students desire. Prerequisites: Students should be comfortable with undergraduate physics, phenomenological thermodynamics and have a solid knowledge of basic undergraduate math (namely, differential equations and linear algebra, although the course requires no math beyond standard undergraduate courses offered for chemistry, physics, and engineering majors). Reasonable proficiency with any programming language is required; Matlab or Python very much desirable. Courses in machine learning required for datadriven course projects (involvement of data science is, of course, optional). 
Alexey Vishnyakov  3  MA030365  
Statistical Mechanics and Kinetics (Term 12)
In this course we will consider a broad range of fundamental topics in statistical mechanics and physical kinetics. We will begin with a review of basic concepts of statistical mechanics and thermodynamics, and will then progress to more advanced themes. These include quantum degenerate gases, phase equilibrium and phase transitions (including Landau theory of second order phase transitions), theory of linear response and fluctuations, and treatment of nonequilibrium phenomena using the Boltzmann kinetic equation. Examples considered in class and homework assignments will focus on applications of the general formalism to physical systems. The course is intended for both experimentalists and theorists.

Anton Andreev 
63 per term

MA060339  
Survey of Materials
Please see the course website for syllabus and other information: http://zhugayevych.me/edu/Materials/index.htm
The course teaches fundamentals of modern Materials Science (Part I of the course) and provides a survey of materials (Part II), covering all relevant Skoltech research areas and beyond, with brief explanation of structural, electronic, physical, chemical or other properties of materials relevant for their practical use, or from the point of view of utilizing their unique properties in applications. It is a core course in Materials Science educational track providing a reference knowledge base for the rest of materialspecific courses as well for student research. 
Andriy Zhugayevych  6  MA060063  
Technology Entrepreneurship: Foundation
Technological innovation requires not only the creation of new inventionsinspired by science, engineering or practicebut also the creation of appropriate organizational vehicles to facilitate real technological impact in society and the environment. After a plausible technical idea has been developed and a potential business concept has been identified, successful commercialization of the technology typically requires the creation of either a new venture or a new unit within an existing organization. This course will explore the creation, development and management of new technology ventures, including private startup companies and other types of business organizations, paying special attention to the role of scientific or technical entrepreneurs as founders or leaders of such ventures.
This course focuses attention on two especially important dimensions of managing entrepreneurial technology ventures: the constant challenge of assembling the resourcesfinancial, human, material and organizational resources, among othersthat are required to operate the business; and the art of iteratively and concurrently managing the processes of technology design, product and/or service design, and market analysis. It has an international perspective as well as a domestic national perspective on entrepreneurship. The backbone of the course is a group project in which student teams conduct a strategic analysis of the entrepreneurial prospects of a novel technology idea, and develop a proposed strategy for a new venture to implement that idea. The course will also include a series of lectures, lively classroom analyses of entrepreneurial technology cases, guest presentations by technology entrepreneurs, various classroom learning exercises, and lively classroom discussion of contemporary topics in technology entrepreneurship. 
Alexey Nikolaev, Dmitry Kulish 
6  E&I  MC060008 
Theory of Phase Transitions (Term 12)
The role of longrange thermal fluctuations in the condensed matter
physics is considered. We give a theory of the second order transitions starting from the Landau expansion in the order parameter. As an introduction we consider the mean field theory, then we take into account fluctuations the role of which can be examined in the framework of the perturbation theory and the socalled renormgroup formalism. The peculiarities of a weak crystallization transition where fluctuations qualitatively change the nature of the phase transition in comparison with the mean field picture are treated on the same diagrammatic language. The theoretical approach based on the Landau expansion is utilized to examine thermal fluctuation effects far from phase transition points. We consider the longscale properties of smectics where fluctuations destroy the longrange order. The smectics are treated in the framework of the renormgroup approach. The same renormgroup technique is developed also for twodimensional ferromagnets where the effective coupling constant increases with increasing scale what drastically change longscale properties of the system. Longrange fluctuations are also relevant for membranes which are twodimensional objects immersed into a threedimensional fluid. Elastic modules of a membrane are logarithmically renormalized, the renormalization law can be found by using renormgroup methods. Of special interest is BerezinskiiKosterlitzThouless phase transition in superfluid, crystal or hexatic films which is related to appearing free point defects (vortices, dislocations or disclinations). The problem can be mapped into sineGordon model and then examined by renormgroup methods. We present some facts concerning critical dynamics and the socalled KPZ (KardarParisiZhang) problem. Then we consider peculiarities of the 2d hydrodynamics and passive scalar. 
Vladimir Lebedev 
63 per term

MA060138  
Topics in Neurobiology Seminar
A research paperbased course.
Overview of current research relating to various ‘hot topics’ in neurobiology and discussion of current research articles on the subject. Analysis of experiments and research described in scientific papers are presented by students and critically discussed by the class led by the instructor. Novel methods in neurobiology – optogenetics, molecular magneto technique, transparent tissues imaging will be discussed in depth. Topics include mapping of the brain and behavior, optogenetic manipulation of memory engrams, mouse models of Alzheimer disease, synaptic plasticity, dendritic spines morphology, pathology, and neurodegenerative diseases. 
Dmitry Artamonov  3  MA030104  
Unconventional Hydrocarbons
The course provides an introduction to unconventional (shale) hydrocarbons as a perspective source of oil and gas. It consists of several parts describing existing oil and gas shale formations in a world and in Russia (Bazhenov, Domanik, Khadum formations), detailed data on lithology, petrophysics, geochemistry and geomechanics of shale rock and modern methods for prospecting, exploration and production of unconventional hydrocarbons. The course includes lectures, seminars and laboratory works. During the course students work individually and in teams compiling a comprehensive data set, analyzing of research results and developing of technological strategy on prospecting, exploration and production of shale hydrocarbons.

Mikhail Spasennykh, Alexei Tchistiakov 
3  DA030189 
Course Title  Lead Instructors  ECTS Credits  Stream  Course Code 

3D Bioprinting: Processes, Materials, and Applications
Threedimensional (3D) printing represents the direct fabrication of parts layerbylayer, guided by digital information from a computeraided design file without any partspecific tooling. Additive manufacturing technology offers significant advantages for biomedical devices and tissue engineering due to its ability to manufacture lowvolume or oneofakind parts ondemand based on patientspecific needs, at no additional cost for different designs that can vary from patient to patient, while also offering flexibility in the starting materials. Bioprinting requires a broad range of expertise from different major disciplines, namely, biology (e.g. tissue and cell behaviors), mechanical engineering (e.g. additive manufacturing, machine design and control and CAD/CAM) and materials science (e.g. biomaterials, fluid behaviour).
The main goal of 3D bioprinting course is thus written to bridge the gaps between the abovementioned three disciplines, providing not only the fundamentals, but practice knowledge. The course starts with the introduction of tissue engineering (TE) and the scaffoldbased TE approaches. Big part of course will be devoted to main processes of 3D biofabrication. We will describe the three key stages in 3D bioprinting, which are preprocessing (biomaterials and cell source), processing (the 3D bioprinting systems and processes) and postprocessing (cell culture). The application areas of bioprinting, including tissue engineering and regenerative medicine, clinics and transplantation, pharmaceutics, and cancer research, the future trends in bioprinting that will revolutionize the organ transplantation technology in the next decades will be discussed. During laboratory class students will get acquainted with the bio additive technologies on various bioprinting installations and biomaterial mechanical testing. 
Igor Shishkovsky  3  MA030354  
Academic Communication: Preparatory English for Phd Exam (Term 12)
Efficient professional communication is the key to Academic success. The course is designed for PhD students who want to maximize their academic potential by boosting their ability to write research papers, present in front of multidisciplinary audiences, participate in scholarly discussions and engage in other forms of academic communication.
The main goal of the course is to enable PhD students to produce clear, correct, concise and coherent texts acceptable for the international professional community. The course is designed for a multidisciplinary audience. The course serves as a preparation for the qualification language exam, which is a prerequisite for the Thesis defense. 
Elizaveta Tikhomirova 
31.5 per term

DE030029  
Advanced Manufacturing of Composite Materials
This course is developed to give students a broad background and hands on experience in manufacturing of advanced composite materials. Both materials and manufacturing methods are discussed. A brief introduction to advanced composite materials and processes is presented. The course is focused on the innovative nonautoclave technologies of thermosetting resin based/fiber reinforced advanced composites. Manufacturing is covered in terms of the major steps required to fabricate laminated composite parts. These will be described and discussed in details and worked out experimentally through conducting a set of lab projects. The following technologies and methods will be covered: Vacuum Infusion, Press Molding, Pultrusion, Filament Winding, and Mechanical Testing. Typical problems of materials, tooling, cure, and technological defects will be discussed.

Alexander Safonov  6  MA060298  
Advanced Molecular Biology Laboratory Practice
This course offers students the opportunity to work individually on laboratory projects assigned by the course instructor. During the term students are expected to have at least one entire working day in the lab, although additional days may be required. Final grades are determined by the students' final presentations, which describe their project/goals along with the results/progress accomplished. Participation in the course requires approval from the students' own advisors, as well as the instructors of the course

Konstantin Severinov  6  DA060046  
Advanced PLM techniques: Testing and Models Validation (Term 56)
This course is final course in PLM series and is devoted to the different types of testing and numerical models validation.
Students learn how to perform vibrational and modal testing in order to identify dynamic parameters of given structure. The modal testing is performed using laser scanning vibrometry. The results of modal and vibrational testing are used for finiteelement model validation and updating for accurate dynamics simulation. Also, so called HardwareintheLoop (HiL) testing is important part of the course. The idea of HiL is to upload the functional model of investigated system to realtime board and test it in combination with physical parts. During the course students perform a number of tests with the system that was designed and prototyped during courses Advanced PLM I and Advanced PLM II. Finally the results are used for system model validation. 
Ighor Uzhinsky 
63 per term

MA030254  
Advanced Quantum Mechanics (Term 12)  Mikhail Feigelman 
63 per term

DA060207  
Advanced Quantum Mechanics (Term 56)  Konstantin Tikhonov, Mikhail Feigelman 
63 per term

DA060207  
Aerosol Science and Technology
The course will introduce the basic phenomena of aerosol science, particle formation in the gas phase and their behavior, concepts and measurement techniques for the aerosol particles. Students will synthesize (carbon nanotubes, NaCl, metal, metal oxide and polymer) nanoparticles by two aerosol techniques: gastoparticle and liquidtoparticle conversions. Students will be trained to operate sparkdischarge aerosol synthesis reactor for production of nanoparticles and singlewalled carbon nanotubes and spray drying and pyrolysis reactors.
The student will perform the online measurements of number size distribution of aerosol synthesized nanoparticles by differential mobility analyzer (size range: 21000 nm). Students will become familiar with processes of the aerosol particle collection (filtration, electrostatic precipitation, thermophoretic precipitation). The produced samples of nanoparticles will be observed with means of transmission and scanning electron microscopies. Totally 34 lecture hours and 15 exercise hours, 5 hours for seminar lessons, 6 presentation hours will be arranged. Students will write a short essay and give a presentation on one of the selected topics. 
Albert Nasibulin  6  MA060300  
Biomedical Innovation and Entrepreneurship
The course aims to provide students with an understanding of applications and practices of biomedical science in an industrial healthcare. To put it simple, we will discuss where and how Skoltech biomedical graduates may employ their skills beyond academy science. To achieve this goal the course will decompose the industry into the value chain of independent but interconnected entities and then make deep investigation of motives, profits, and costs of any segment/entity of this value chain. The incomplete list of such entities will include: R&Ddriven startups, CROs, CMOs, regulators, integrated pharmas, marketing agents, distributors, retail, hospitals, doctors. The emphasis will be made on the value chain groups that are immersed into the challendge of transforming high technologies into the tangible patient benefit, from hardcore drug development to all kinds of medical devices and services. Such challenges will be taught through development of the group project that will be developed through the stages of Problem statement (indication, regulation, POC and QC), preclinical design, clinical design, manufacturing/delivery design and final integrative presentation.

Dmitry Kulish  3  E&I  MC030013 
Classical Integrable Systems (Term 56)
Course description: A selfcontained introduction to the theory of soliton equations with an emphasis on their algebraicgeometrical integration theory. Topics include:
1. General features of the soliton systems. 2. Algebraicgeometrical integration theory. 3. Hamiltonian theory of soliton equations. 4. Perturbation theory of soliton equations and its applications to Topological Quantum 
Igor Krichever 
63 per term

MA060179  
Computational Chemistry and Materials Modeling
The course provides an overview of modern atomistic computer simulations used to model, understand, and predict properties of realistic materials. The emphasis is on practical techniques, algorithms and programs to bridge theory and applications, from the discovery of materials to their use in realworld technologies. This introductory course is intended for both theoreticians and experimentalists in modern Materials Science at academic level ranging from MSc students to PhD students and postdocs.

Andriy Zhugayevych  6  MA060008  
Computational Materials Science Seminar (Term 28)  Dmitry Aksenov 
30.5 per term

MA030430  
Condensed Matter Spectroscopy and Physics of Nanostructures (Term 1B4)
This course presents a modern introduction to the field of optical phenomena in condensed matter and nanostructures. The first part of the course starts from the classical and quantum theory of electromagnetic response, and basics of the condensed matter spectroscopy. Then the major research directions in the modern condensed matter spectroscopy are considered, such as spectroscopy of graphene, topological materials, and twodimensional transition metal dichalcogenides. The second part of the course is focused on specific optical phenomena in semiconductors, heterostructures, nanostructures and interfaces, such as surface plasmons and polaritons, excitons, spinorbit coupling effects, Raman scattering and color centers.

Alexey Sokolik 
61.5 per term

Options  MA060313 
Continuum Mechanics (Term 23)  Robert Nigmatulin 
63 per term

DA060181  
Convex Optimization and Applications
This course introduces the basic theory in convex optimization and illustrates its use in recent successful applications such as sparse learning, blind source separation, lowrank optimization, image processing, regression and classification, phase retrieval.
Through the course, students will study convex sets and functions and their properties, duality and dual maximization problem with the same optimal value, a certificate of optimality for an optimization problem. Students will also learn some commonly known convex optimization forms such as Linear Program, Quadratic Program, Second Order Cone Programs, SemiDefinite Programs etc. Students will know practical tools, and able to recognize and formulate convex optimization problems and solve them using efficient solvers. 
AnhHuy Phan, Andrzej Cichocki 
3  MA030136  
Critical Points of Functions (Term 12)
The theory of critical points of functions is of the main subjects of Singularity theory studying local geometry of singularities of differentiable maps as well as its relationship with global topological invariants of manifolds.
In the course we will discuss classification of critical points, its relationship with the ADEseries of simple Lie algebras and the corresponding reflection groups, their deformations and adjacencies. The study of a local topological structure of singularities will include description of Milnor fiber and vanishing cycles. We will discuss also application of the theory critical points to the study of caustics and wave fronts in geometric optics and classical mechanics, as well as enumeration of contact singularities in complex projective geometry. 
Maxim Kazarian 
63 per term

Options  MA060424 
Digital Signal Processing
Digital signal processing (DSP) refers to various techniques for improving the accuracy and reliability of digital communications. The goal, for students of this course, will be to learn the fundamentals of Digital Signal Processing from the ground up. Starting from the basic definition of a discretetime signal, we will work our way through Fourier analysis, filter design, sampling, signal statistics estimation theory, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. We will also deal with modulation, synchronization and propagation channel modes. Handson examples and demonstration will be routinely used to close the gap between theory and practice.
The extra topics covered in this course are: – Fundamentals of random signal theory and analysis; – Modeling communication signals as random processes; – Baseband signal processing, signal synthesis and filter design for communication; – Statistical signal processing in communication; It is hoped that through learning this course students will be equipped with a clear picture of DSP as well as a necessary foundation for further study of advanced DSP topics in the future. 
Andrey Ivanov  6  MA060255  
Efficient Algorithms and Data Structures
Design and analysis of algorithms and data structures is a core part of Computer Science and is of fundamental importance to all application areas. The goal of this course is to provide a representative sample of advanced algorithmic notions and techniques that constitute a modern toolbox for solving reallife problems. We will mainly deal with basic discrete objects – sets, trees, graphs, strings, … – and present efficient data structures and algorithms for solving various basic problems on these objects. Therefore, this course can be viewed as a basis for more specialized subjects. Lecture part of the course will focus on principles and ideas as well as on their mathematical justification. The practical part will include two inclass projects as well as several programming exercises assigned for homework. Those will strengthen practical problem solving skills using techniques taught in the course.

Gregory Kucherov  6  MA060270  
Elliptic Operators in Topology of Manifolds (Term 12)
We plan to discuss two topics, which are central in topology of smooth manifolds, the hcobordism theorem and theory of characteristic classes. The hcobordism theorem proved by S. Smale in 1962 is the main (and almost the only) tool for proving that two smooth manifolds (of dimension greater than or equal to 5) are diffeomorphic. In particular, this theorem implies the highdimensional Poincare conjecture (for manifolds of dimensions 5 and higher). Characteristic classes, in particular, Pontryagin classes are very natural invariants of smooth manifolds. Computation of characteristic classes can help one to distinguish between nondiffeomorphic manifolds. We plan to finish the course with the theorem by J. Milnor on nontrivial smooth structures on the 7dimensional sphere. This theorem is based both on methods of Morse theory and theory of characteristic classes

63 per term

MA060258  
Energy Colloquium
The Energy Colloquium educates the audience in the presentday research and applications within the broader field of Energy Science and Technology. The Colloquium consists of a series of presentations by invited academic and industry speakers. The presentations target a nonspecialist audience.
All Master and Ph.D. students within the Energy Program are encouraged to attend the Energy Colloquium during the entire period of their studies. Students can earn 1 credit, if he/she participates in the Energy Colloquium over the course of any 2 terms of the academic year. Students who passed one round can make next (for credit) over the course of their subsequent studies. 
Alexei Buchachenko  1  Extra  MF010092 
Energy Systems Physics and Engineering
Classical equilibrium thermodynamics is a theory of principles, which provides a framework to study means to produce motive power and useful heat, crucial for our everyday life. It is a pillar of any serious physics and engineering curriculum. This graduate course provides the students from possibly diverse backgrounds with the theoretical concepts that underlie the physics of energy conversion at the heart of heat engines operation, including chemical processes, and the specific knowledge of energy technologies in use nowadays. Covering some of the main realworld technologies for the generation of electric/mechanic, heating and cooling power: boilers, steam and organic Rankine cycles, gas turbines, internal combustion engines, heat pumps and chillers to name a few, students will learn to critically analyze and assess these technologies to improve their performance and imagine innovative and commercially viable solutions to energy problems, accounting for costs and environmental aspects like pollutants formation and their abatement.
Essential notions which are taught include: energy conversion; heat transfer; work; first and second principles; working fluids and thermoelastic coefficients; chemical reactions; thermodynamic cycles; motors and refrigerators: engines and heat pumps; sources of irreversibility; finitetime thermodynamics. Time permitting, notions of kinetic theory and statistical thermodynamics may be briefly introduced. The course is organized around the learning of essential concepts and an awareness development of current energy technologies. It is based both on "teaching with lecture" and "teaching with discussions" methods. In addition to home assignments and project, students will solve problems during tutorials and discuss their solutions, and also perform some experimental activity in the Thermal Lab. 
Henni Ouerdane  6  MA060001  
English Toolkit (Term 1B2)
The goal of the English Toolkit course is to activate Academic English skills required for successful education at Skoltech.
The students will practice Academic vocabulary and grammar, as well as boost their reading, writing and speaking skills. The blended format includes a weekly online workload plus an offline group tutorial providing a flexible and individualised learning trajectory. Realtime feedback in online exercises will be complimented by tutor feedback for the writing and speaking assignments. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030001 
English. Candidate Examinations
This is a blended metacourse for the English Qualification Exam needed for the Russian PhD Degree. The Exam is designed as a multidisciplinary conference where the participants present results of their PhD research and follows the general principles of conference materials submission, peer review, resubmission, presentation, and discussion.
The goal of the Exam is Academic Communication, so the participants should demonstrate the ability to present their research results in front of a multidisciplinary audience and deliver the key ideas in good Academic English in terms of vocabulary, grammar and style. Preexam/ preconference activities, such as material submissions and peer reviews, last of three weeks and take place fully online. They include: Project proposal V1+ 2 Peer Reviews; a 2minute video annotation V1 + peer review; and a stack of presentation slides V1+ peer review. Version 2 of the Proposal, video annotation and the slides should be improved using the comments of the Instructor and the peers. Depending on the applicable regulations related to COVID19, on the Examination day students make their presentations and participate in the discussion in person or via an online platform in front of the Examination Committee and a group of peers. Failure to submit an assignment by the due date may result in the loss of the grade. The participants will practice a variety of academic skills: – Planning and designing a wellstructured and balanced presentation The grade is counted towards the PhD Qualification. 
Elizaveta Tikhomirova  3  DE030003  
Evolutionary, Population and Medical Genomics
Nothing in biology makes sense except in the light of evolution. This course introduces the fundamentals of evolutionary science as applied to genomics. It will allow to see how the basic population genetics processes create, maintain and affect variability in populations and lead to their changes with time. The focus will be on molecular evolution, i.e., the manifestation of these processes in genomes. As humans, we will be particularly interested in evolutionary aspects of medicine. The course assumes no prior familiarity with evolutionary biology, although knowledge of the basics of molecular biology and genetics is expected. The themes covered will include basic concepts in evolutionary biology and generalizations in evolutionary genomics; population genetics and factors of microevolution; and basics of quantitative genetics.

Georgii Bazykin  6  MA060222  
Fundamentals of Optics of Nanoscale Systems (Term 1B4)
The course focuses on the general concepts and experimental developments in the rapidly evolving field of the modern physics of nanosized systems. It covers a broad spectrum of optics on the nanometer scale, ranging from fundamental nanoscience to nanotechnology applications. Topics covered include: foundations of lightmatter interaction at nanoscale, concepts of nearfield and quantum confinement, nanoplasmonics, optical emission of pointed nanoparticles (fluorescent molecules, quantum dots, plasmonic nanoparticles et al). Various experimental methods that used in nanooptics and nanoscience, including nearfield and farfield optical microscopy of subdiffraction spatial resolution, are presented. Nanophotonic devices, photonic crystals, spasers, singlephoton sources, nanosensors are discussed. Seminars assume the discussion of papers presenting a physical basis for nanoscale optical phenomena, as well as the papers describing the last achievements in the area.

Yuri Vainer 
61.5 per term

Options  MA060437 
Fundamentals of Photonics
This course is aimed for the first year master students, and provides an overview of the main physical principles of photonics and photonic devices. The emphasis is made on the demonstration that the light matter interaction in photonic devices can be modified by means of the modern technology. The course give the illustration how the basic physical laws help to get qualitative understanding of different branches of photonics such as light emission, transmission and detection. This introductory course is designed for both theoreticians and experimentalists.

Nikolay Gippius  6  MA060160  
Fundamentals of Power Systems
This course covers power systems analysis & operations, including fundamentals (balanced threephase power) steadystate analysis (power flow), state estimation, operation (optimal power flow), security (contingency analysis and securityconstrained optimal power flow), distribution grid operation, and challenges and trend of future power systems. After successfully completing this course, the student will be capable of analyzing the technical and economic operation of an electric energy system.

David Pozo  6  MA060007  
Geometric Representation Theory (Term 12)
Geometric representation theory applies algebraic geometry to the problems of
representation theory. Some of the most famous problems of representation theory were solved on this way during the last 40 years. The list includes the Langlands reciprocity for the general linear groups over the functional fields, the LanglandsShelstad fundamental Lemma, the proof of the KazhdanLusztig conjectures; the computation of the characters of the finite groups of Lie type. We will study representations of the affine Hecke algebras using the geometry of affine Grassmannians (Satake isomorphism) and Steinberg varieties of triples (DeligneLanglands conjecture). This is a course for master students knowing the basics of algebraic geometry, sheaf theory, homology and Ktheory. 
Mikhail Finkelberg 
63 per term

MA060271  
High Performance Python Lab
This course is devoted to learning how to use Python for High Performance Computing on different architectures – multicore CPUs and general purpose GPUs.
The course is oriented on practical knowledge, where the students will get a handson experience with Python code profiling, modern Python frameworks, such as Python MultiProcessing, Numba, Cython, mpi4py, PyCuda and others. Wide range of problem sets from linear algebra, image processing, deep learning, physics and engineering makes this course interesting and suitable for all levels of students from all CREIs. Students will also get the possibility to work on modern supercomputers. 
Sergey Rykovanov, Daniil Stefonishin 
3  MA030367  
History and Philosophy of Science. Candidate Examinations  Ivan Lupandin  6  DE060026  
Ideas to Impact: Foundations for Commercializing Technological Advances
Technological innovation is critical to the survival and competitiveness of emerging and existing organizations. This course lays the foundation to undertake a robust analysis and design of opportunities for technologybased commercialization. We introduce tools and frameworks that help isolate and control the factors shaping the identification, evaluation and development of commercial opportunities. Throughout the course we use technology examples originating from problem sets found in engineering and scientific education to develop the skills necessary to connect technology and impact.
At the same time, through creativity lab students will be introduced to a variety of creative problem solving techniques and learn how to apply these techniques in the context of the development, evaluation and application of ideas and concepts with commercial potential; consider the evaluation of business ideas that translate existing business models into new national contexts. The course is designed to help students develop the ability to find, evaluate, and develop technological ideas into commercially viable product and process concepts, and build those concepts into viable business propositions. The material covered is research and theorybased but the course is practiceoriented with much of the term spent on shaping technologybased opportunities. A central objective of this subject is to equip students with an understanding of the main issues involved in the commercialization of technological advances at both strategic and operational levels. 
Zeljko Tekic  6  E&I  MC060002 
Industrial Robotics
Industrial robots are used to do repetitive actions in various different manufacturing processes. They are automated, programmable and can be integrated with various external devices depending on the solving problem. Typical applications of industrial robotsmanipulators include welding, painting, assembly, moving, palletizing, product inspection processes accomplished with high speed and precision.
The main goal of this course is explain principles of controlling robots and solve different automation tasks demanded in industry. In this course, a wide range of questions will be addressed, beginning from the basics of robot teaching and controlling up to integration of manipulators and external devices into a single system. During laboratory class we will get acquainted with modern industrial robots. Students will be able to control an teach robots for solving different tasks: from simple movement of manipulators up to build an automated system for real manufacturing task 
Igor Shishkovsky  3  MA030249  
Innovation and Intellectual Property Studies Doctoral Seminar (Term 25)  Kelvin Willoughby 
61.5 per term

E&I  DC060009 
Introduction to Blockchain
This course provide an overview of modern blockchain technology and its' practical applications (Cryptocurrency, Certification, Anchoring. Industrial examples.) We will start from basic cryptography and distributed data base systems and show how these tools are used in blockchain. The covered topics are the following:
) Introduction to cryptography, type of ciphers. Private and Public crypto systems 
Alexey Frolov, Yury Yanovich 
3  MA030272  
Introduction to Computer Vision
Computer Vision is one of the most rapidly evolving subfields of Computer Science with many applications, e. g. in autonomous driving and healthcare, among others. This course is designed to provide a comprehensive systematic introduction to the field. We'll start with the recognition of some simple object elements such as corners and edges and then proceed to the detection of more complex local features. All major problem statements such as image classification, object detection and segmentation as well as the corresponding classical algorithms will be covered within the course. Finally, we'll briefly introduce convolutional networks and discuss key deep learning architectures for the same set of problems.
We'll extensively use Python and CV & image analysis libraries scikitimage and OpenCV during handsons and homeworks. The final grade will be calculated using the results of three homeworks (20% each) and the final project (40%). 
Mikhail Belyaev  3  MA030348  
Introduction to Life Sciences program
Professors from the Life Science Center will tell about their labs and research projects. This course will help students to select a lab of their interest and a future research adviser.
The information about the Life Science labs is here: https://crei.skoltech.ru/cls/researchprojects/currentprojects/ As final project students should select one topic from the professors' lectures;find the professor's papers on this topic, read and analyze them (twothree most important/interesting ones)also, find some interesting papers from other groups, to get a contextwrite an essay / review (if you have ideas about what else could be done in the selected area, add them) – about 23 pages. The final schedule (what lecture reads which professor, and when) will be available by the end of the September. 
Mikhail Gelfand  3  MA030371  
Introduction to Linux and Supercomputers
The course is devoted to series of frequently asked questions from people who start their scientific computing life with Linux. We'll give a masterclass for a work within the sshsession, standard terminal commands and their combinations, tips on organization of the simplest possible bashscripts (loops, background calculations, IOredirections, etc.).
We'll explain and demonstrate the gentleman's set for software compilation from source (user configuration files, environment variables, Makefiles basics, compiler options and optimization flags, linking external libraries and connection of these concepts). We'll describe then the very basic points of hard and software architectures of modern computing systems. And in the end of the day we'll present the model project based on all the concepts above. Lecturers expect that after the course student will be able to login on the HPCcluster, properly setup the environment, compile the source code, run parallel programs on HPCsystems and write scripts for data postprocessing. 
Sergey Matveev  3  MA030366  
Introduction to Plant Biology
General biological courses give knowledge of eukaryotic features basing on processes in animals. Plants are out of focus as usual. This course aims to fill the gaps and show the plant specificity. The main purpose of the course is to consider the plant features that are absent in animals or that differ substantially from animal analogs. The characteristic features will be analyzed in plant biochemistry, cell organization and at the level of a whole organism. Last section will be devoted to applications in contemporary biotechnology. The course does not pretend to draw comprehensive picture of plant life; the focus will be on most important traits required to deep understanding of basic eukaryotic processes. Consequently, the general knowledge in eukaryotic biochemistry and cell biology is the prerequisite for this course.

Eugene Lysenko  3  MA030261  
Introduction to Product Lifecycle Management (PLM)
Basic course for 1st year MSc students devoted to PLM as applied to product development. Lectures are devoted to an overview of current trends in industry digitalization, “digital twins” technology and modern implementation of computeraided design, computeraided engineering, computeraided manufacturing, modelbased systems engineering, product lifecycle management, multidisciplinary optimization, predictive and prescriptive maintenance. Practical classes are dedicated to the simulationdriven product development process in a particular case study. Students learn how to develop a highlevel model of a complex system, split it into subsystems and connect it with the functional models of each subsystem and with preliminary 3D models (e.g. aerodynamics and structural analysis). Also, the optimization of the whole system plays an important role in the course. The case study is a challenging task like HighAltitude Pseudo Satellite or TrussBraced wing aircraft) Thus, during the course students go through all the main stages of complex system development process.

Ighor Uzhinsky, Sergei Nikolaev 
6  MA060148  
Introduction to Quantum Groups (Term 12)
Quantum groups were introduced in the mid80's and very quickly became one of the most important topics in mathematics and mathematical physics. They are still actively studied, and their knowledge is necessary for work in many areas.
The purpose of the course is an introduction to quantum groups. The content will be based on classic works of the 80's and early 90's, we will not get to the latest results. Initial knowledge about quantum groups is not assumed, but acquaintance with Lie algebras and Groups, Poisson brackets, and the first notions of category theory is assumed. 
Mikhail Bershtein 
63 per term

Options  MA060426 
Introduction to Solid State Physics
This course gives an introduction to solid state physics, one of the cornerstones on which a modern technologies are based. We will begin with the conventional classification of solids on the basis of binding forces, to be followed by crystal structure description and experimental techniques for crystal studies. From there we will discuss classical and quantum aspects of lattice dynamics and begin the study of the electronic structure of solids, including energy band formalism and carrier statistics in metals, semiconductors and insulators. Next we will consider basics of the atomic and electronic processes at crystal surfaces and interfaces, kinetic effects and scattering of the electrons. We will continue with the study of the optical processes in solids, including nonequilibrium carrier dynamics and photovoltaic effects and their applications in technology.

Sergey Kosolobov  6  MA060027  
Introduction to Surface Physics
This course assumes the study of techniques able to provide information concerning electronic and atomic surface structure. The techniques can be applied to materials and nanostructures research. The students should learn how the surface is arranged, what are the specific properties of the surface, what processes occur at the surface and interfaces, including metalsemiconductor interface and some other interfaces typical for heterostructures. Adsorption, interfacial reactions and films growth are also considered. Vacuum techniques of surface characterization are accented.

Andrey Ionov  3  Options  MA030218 
Introduction to the Quantum Field Theory (Term 12)
Introduction to basic notions of gauge theory: gauge invariance, SU(N) Lie algerbras and their representations, Yang Mills Largangian and its quantization, FaddeevPopov method, ghosts and unitarity, diagram technique, basics on perturbation theory, analysis of simplest Feynman diagramms, beta function in nonabelian YangMills theory, renormalization group, asymptotic freedom, Higgs mechanism, basic notions of QCD and electroweak theory. Depending on progress: some advanced topics: anomalies, instantons.

Yaroslav Pugai 
63 per term

MA060273  
Introduction to the Theory of Disordered Systems (Term 12)
This course is mainly dealing with the quantum electronic properties of disordered materials. I start with a review of different types of disorder and general methods of their theoretical treatment. Then I give a detailed discussion of the two popular models of quenched disorder, widely used for description of quantum solid state systems: Anderson model and Lifshits model. I discuss the properties of the disordered systems in the insulating phase: the density of states, the tails in the optical absorption ( with the optimal fluctuation method) and different versions of hopping conductivity: the nearest neighbour hopping and the Mott's variable range hopping. I also take into account the longrange Coulomb correlations and derive the Coulomb gap in the density of states and the EfrosShklovskii law for the conductivity.
As to the vicinity of the metalinsulator transition, I give a qualitative discussion of the mechanism behind the transition, as well as the most powerful tools for probing the properties of the system near the transition: analysis of inverse participation ratios and the concept of multifractality of the wavefunctions. In the metallic phase I discuss the weak localization corrections, including magnetoresistance, inelastic phasebreaking mechanisms and interactioninduced anomalies in the density of states near the Fermi surface. At the end of the course I give a brief introduction to mesoscopics, including the Landauer formalism and quantization of the ballistic conductance. 
Alexey Ioselevich 
63 per term

MA060274  
Laser Spectroscopy (Term 1B4)
Spectroscopy is a science of studies of the quantum objects using the light. Before the laser era, its methods were limited to the spectroscopies of emission, absorption, and Raman scattering. The subject of the present course is not so much an improving, using the lasers, performance of the classical approaches (although this also is mentioned) but rather learning the new (more than a dozen) methods that have become possible only due to the appearance of the lasers. The course provides knowledge of the fundamental processes in spectroscopy as well as the methods allowing one to solve the problems that require (i) ultrahigh sensitivity, (ii) ultrahigh selectivity, (iii) ultrahigh spectral resolution, and (iv) ultrahigh temporal resolution. As an elective, the effects of quantum interference are considered such as coherent population trapping, the Autler–Townes effect, electromagnetically induced transparency, lasing without inversion, and more.

Alexander Makarov, Alexey Melnikov 
61.5 per term

Options  MA060212 
Magnetic Phenomena at Macro, Micro and Nanoscales
Objectives of this course are as follows: the mastery of the fundamental concepts, laws, experimental results and theories of the rapidly developing field of spintronics. Spintronics involves study of active control and manipulation of spin degrees
of freedom in solidstate systems. The primary focus of the course is on basic physical principles underlying the generation of carrier spin polarization, spinpolarized transport in metals, semiconductors and insulators and spin dynamics. The basic principles are illustrated by direct calculations in the framework of simple and transparent physical models. A number of problems are suggested for individual work followed by subsequent group discussions. 
Lyudmila Uspenskaya  3  Options  MA030219 
Master Your Thesis in English (Term 56)
The key to efficient professional communication is the ability to convey ideas clearly, coherently and correctly both orally and in writing.
The Course offers concise and practical guidelines for writing and defending a Master Thesis at Skoltech. The course focuses on the main parts of the Thesis in terms of structure, vocabulary and grammar, and their transformations for a presentation with slides. Students will develop a conscious approach to own writing and presentations through thorough analyses of the best authentic examples combined with intensive writing and editing practice. The ‘processforproduct’ approach teaches the students to write – use (peer) reviewer’s advice – revise/edit – repeat, and creates linguistic awareness needed to avoid the typical pitfalls. The Course is offered in two modules which gradually build on the necessary writing and presentation skills. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030003 
Master Your Thesis in English 1 (Term 5B6)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030003ls 
Materials Chemistry  Keith Stevenson  6  DA060042  
Materials Selection in Design
This course illustrates the need for a scientific and practical method of selection of appropriate materials for industrial application. It includes review of the principles of materials science including materials classification, hierarchical structuring, related properties, and performance of different class of materials such as natural materials, metals, ceramics, plastics, cellular solids. Ashby’s material selection algorithm for rational selection of materials for specific applications will be taught here in comprehensive way – analysis of function, objectives and constraints, deducing of performance indices. All the concepts covered in lectures will be practiced by using a commercially available software known as CES EduPack to implement data intensive learning. Team projects are aimed to taste the CDIO approach in Materials Selection.

Alexey Salimon  3  MA030099  
Mathematical Methods in Engineering and Applied Science (Term 12)
The course introduces students to mathematical methods widely used in modern engineering and applied sciences. It consists of three main parts: 1) Methods of Applied Linear Algebra (solving linear systems, LU, QR, SVD, and other factorizations, Principal Component Analysis, iterative methods, FFT, least squares, pseudoinverse, etc.); 2) Statistical Methods and Data Analysis (mean, variance, probability; moments, covariance, Gaussian processes, Markov chains; regression, gradient descent; neural networks, machine learning); and 3) Applied Differential Equations (linear and nonlinear ordinary differential equations, stability and bifurcations of solutions, linear and nonlinear partial differential equations, hyperbolicity, characteristics, dispersion, reactiondiffusion phenomena, pattern formation).
The course is introductory by nature, covering a wide range of topics and methods of modern interest in applications. Its theoretical content is informal in style and most of the concepts will be illustrated with problems from engineering, physics, chemistry, and biology using numerical computations in Matlab and Python. The three parts of the course are aimed at: part 1 – using the right language that is crucial for understanding many computational techniques used in engineering; part 2 – learning important tools of analysis of results obtained either by computation or in experiments; and part 3 – learning the nature of key mathematical models that form the foundation of engineering and applied sciences. 
Aslan Kasimov 
63 per term

MA060352  
Mathematical Methods of Science (Term 12) The course is addressed to undergraduates of the first year and contains applications of various mathematical methods for solving problems of mathematical physics. The course assumes a minor familiarity with basic notions of classical mechanics and field theory on the example of solving specific problems. The main purpose of the course is to encourage undergraduates to independent research work. For this reason, the main element of the course is an independent solution to the problem, requiring the study of additional material. In the endpoint the students are assumed to acquire the use of Green functions, distributions, Laplace and Fourier transforms, asymptotic evaluations in mathematical physics 
Sergei Khoroshkin 
63 per term

Options  MA060317 
Mathematical Modeling in Biology
The course aims to teach students to quantify biological observations into conceptual models, frame these models in mathematical terms, and analyze these models, both qualitatively and numerically.
It includes considering strategies to choose the relevant variables, parameters and observables, model nature (e.g. discrete vs continuous), modeling technique (e.g. agentbased simulations vs. dynamical system approach), and visualization and interpretation of the results. The following classes of systems will be used as examples: 1. Population models 
Yaroslav Ispolatov  6  MA060033  
Micromechanics
Micromechanics studies heterogeneous materials. They may be manmade (concrete, metals, composites, coatings) or naturally occurring (porous and cracked rocks, bone). Matrix composites – continuous matrices containing various inhomogeneities (pores, cracks, fibers, foreign particles) – constitute an important example. The goal of micromechanics is to relate the physical behavior of such materials – in particular, their overall (effective) properties – to the microstructure (geometric arrangement of the constituents and their properties). The course focuses on two groups of effective properties: the elastic and the conductive ones. The course covers the following topics:
Tensorial algebra Background results on elasticity and thermal/electric conductivity. Quantitative characterization of microstructure. Isolated inhomogeneity problem (Eshelby problem) in the context of elasticity and thermal or electrical conductivity. Property contribution tensors for effective elastic, thermal, and electric properties. Effective properties of heterogeneous materials: Variational bounds Noninteraction approximation Differential scheme Effective field approaches Crossproperty connections. The lectures will be supplemented by weekly homework assignments and quizzes. Students will be evaluated on the basis of the final written exam. 
Sergey Abaimov  3  MA030247  
Modeling of Multiphase Flows
This is a course into foundations of the Multiphase Flow Modeling.
We consider the basics of the multiphase flow modeling, including the multicontinua approach, the derivation of the multiphase flow models from first principles (mass and momentum conservation laws) within the multifluid approach. Closure relations for suspension rheology and particle settling are discussed. Small scale phenomena are considered: particle migration, and bridging, transition to close packing. We specifically consider multiphase flows in reservoir, fracture and well, as applied to oil production technologies. 
6  MA030344  
Models of Sequential Data
In this course, we discuss the forefront of modern research in learning from sequence data. The course takes a walk from the basics of sequence processing to modern deep learning approaches. We aim at covering both fundamental and modern advances in this area not commonly discussed in undergraduate or graduate Machine Learning and Deep Learning classes.
Over multiple weeks, we will investigate how researchers and practitioners use these methods and algorithms for analyzing timeseries data, text data, or medical sequences. The course aims to bring all students on the same page. They do not require severe background knowledge. The objective is to provide them with both depth and breadth knowledge of the stateoftheart in sequence modeling. 
Alexey Zaytsev  3  MA030433  
Modern Plant Breeding  Laurent Gentzbittel  6  MA060401  
Modern Wireless Systems  5G and Beyond
The course is an introductory course in which students are expected to gain an understanding of the main principles and technological basis of the new wireless communications technologies, first of all, cellular. The course will discuss the main trends in the development of new generations of cellular communications, primarily 4G and 5G, as well as the basic prerequisites and requirements for creating a 6G system.
The course will include: This course is designed to provide students with the necessary functional knowledge possible in the shortest possible time. 
Dmitry Lakontsev  3  MA030410  
Molecular Spectroscopy (Term 1B2)
The spectra of molecules provide unique information about the structure and properties of substances that can be used to accurately determine the composition of the atmospheres of planets and interstellar medium, to analyze the causes of global warming and to estimate the thickness of the Earth’s ozone layer, to detect impurities in pure gases and liquids, to detect toxic and explosive substances, to study the biological activity of molecules, etc. The course examines the physical phenomena leading to the occurrence of absorption, emission or scattering spectra, the structure of these spectra due to rotations, vibrations and changes in the electronic state of molecules, as well as questions of the experiment, the various types of spectrometers, data processing methods.

Leonid Surin 
31.5 per term

Options  MA030209 
Nanocomposites
The focus of the course is a special class of composites which include nanoscale reinforcements. Such nanoreinforced materials can be classified in two groups:
1. Nanocomposites which have reinforcing phase of nanodimensions (carbon nanotubes (CNT), graphene and graphenerelated materials (graphene oxide etc), nanoclays and some others. For both types of nanocomposites the course covers their production, microstructure, micromechanics, functional properties (electrical and thermal conductivity) and applications. There has been immense interest in the use of carbon nanomaterials for reinforcement of plastics and their composites in the recent years. The course provides to Skoltech students an opportunity to catch with this accelerated trend of worldwide research. 
Sergey Abaimov  6  MA060329  
Neuroendocrynology  Yuri Kotelevtsev  3  MA030402  
Numerical Linear Algebra
Numerical linear algebra forms the basis for all modern computational mathematics. It is not possible to develop new large scale algorithms and even use existing ones without knowing it.
In this course I will show, how numerical linear algebra methods and algorithms are used to solve practical problems. Matrix decompositions play the key role in numerical linear algebra. We will study different matrix decompositions in details: what are they, how to compute them efficiently and robustly, and most importantly, how they are applied to the solution of linear systems, eigenvalue problems and data analysis applications. For largescale problems iterative methods will be described. I will try to highlight recent developments when it is relevant to the current lecture. This course should serve as a basis for other IT Skoltech courses. It will also serve as a firsttime place where programming environment and infrastructure is introduced in a consistent manner. 
Ivan Oseledets  6  MA060024  
Parallel Computing in Mathematical Modeling and DataIntensive Applications (Term 56)
This interdisciplinary course:
— makes the students familiar with main scientific and engineering applications of modern supercomputers, — explains numerical methods behind the applications and their implementation — discusses efficiency of the common algorithms on modern supercomputer architectures — extends students background in modern processors and supercomputer architectures The applications includes computations fluid dynamics with finite difference and finite volume methods, Lattice Boltzmann and cellular automata, finite elements modeling, molecular simulations, plasma, quantum chemistry, distributed deep learning on multiple computing devices, processing big volumes of data (e.g. large graphs) on distributed systems. Each topic includes a lecture by a lead instructors, invited highprofile guest lecturers and students. Each lecture is devoted to a particular application. Students will form teams to work on projects in one of the application areas and then share their experience with the fellow students at seminar sessions and a final project presentation at the conclusion of the course. 
Sergey Rykovanov, Alexey Vishnyakov 
63 per term

MA060411  
Pedagogical Experience  Dmitry Artamonov  3  DE030005  
Permafrost and Natural Hydrates
This course is about permafrost and natural hydrates. You will learn The course is devoted to the consideration of cryogenicgeological conditions of the northern oil and gas provinces of Russia and their influence on the construction and operation of production wells. The course includes permafrost characterization within the main oil and gas fields in the European North and Siberia, including the Arctic zone. The main cryogenicgeological processes occurring in the areas of permafrost propagation are considered. The description of gas and gas hydrate accumulations in permafrost is given. The conditions for the formation and existence of gas and gas hydrate accumulations in permafrost are analyzed. Zoning of the territories of oil and gas provinces on the complexity of geocryological conditions for the development of deposits is carried out. The characteristic of engineering and permafrost studies for the selection of construction sites for producing wells is given. Analyzed the complications arising from the construction and operation of wells in permafrost. Thermal and mechanical interaction of producing wells with permafrost is considered. The behavior of gas hydrate accumulations in permafrost zone during the development of gas and oil fields in the Arctic is analyzed. The impact of global climate change on the stability of wells and ground engineering structures of the oil and gas complex is assessed.

Evgeny Chuvilin  3  MA030343  
Phase Transitions: Introduction to Statistical Physics and Percolation (Term 12)
This is a course on rigorous results in statistical mechanics, random fields, and percolation theory. We start with percolation, which is the simplest system, exhibiting singular behavior, and undergoing phase transitions. We then go to more realistic models of interacting particles, like the Ising model and XYmodel, and study phase transitions, occurring there.
The topics will include: Percolation models, infinite clusters. Crossing probabilities for rectangles Critical percolation The RussoSeymourWelsh theory Cardy’s formula in Carleson form and the Smirnov theorem. Gibbs distribution DobrushinLanfordRuelle equation Ising model Spontaneous symmetry breaking at low temperatures O(N)symmetric models The Mermin–Wagner Theorem The Berezinskii–Kosterlitz–Thouless transition Reflection Positivity and the chessboard estimates Infrared bounds 
Semen Shlosman 
63 per term

MA060427  
Physics of Partially Disordered Systems
Principle notions and phenomena being specific for partially ordered media and amorphous state are considered. Examples and illustrations are provided for liquid crystals, plastic crystals (rotary crystals), nanocrystals, and partially ordered polymer structures. Phase transitions in these systems are accented, as well as the role of defects and dislocations. Optical properties of partially disordered systems are addressed. The systems consisting of nm and submkmsize particles are also discussed.

Pavel Dolganov  3  Options  MA030215 
Physics of Semiconductor Bulk Crystals and Nanostructures
The course focuses on the presentation of foundations of the modern physics of semiconductors. Along with the traditional branches (band theory, phenomena in the contacts, single particle excitations and interparticle interactions) developed for bulk semiconductors, the course includes the problems of composite quasiparticles and collective excitations in low dimensional semiconductor nanostructures (quantum wells, quantum wires and quantum dots) and microcavities. The basic principles and features of semiconductor lasers are also addressed.

Vladimir Kulakovsky  3  Options  MA030214 
Practicum in Experimental Physics
This course assumes mastering in certain experimental techniques in physics, including a practical work with experimental setups. The course is practically oriented, with small share of lectures. Students will have an opportunity to conduct individual research project and be familiar with unique stateoftheart equipment.
The work can be starteded in Term 4, or can be continued after participation in Term 2. For SkoltechMIPT net program, both Term 2 and Term 4 are obligatory from MIPT side, but can be substituted with other courses in frames of individual MIPT plan. 
Valery Ryazanov  6  Options  MA060208 
Principles of Applied Statistics
Standard courses in mathematical statistics focus on classical statistical methods. However, in practice, modern statistical methods are often used, for example, bootstrap, nonparametric estimation, smoothing based on decomposition in orthogonal bases, methods for reducing dimensionality and sensitivity analysis, etc. Understanding the theory underlying these methods, as well as the ability to apply them in practice, is absolutely necessary for anyone working in mathematical statistics and data analysis.

Maxim Panov  3  MA030416  
Quantum Mechanics (Term 12)
Advanced course in quantum mechanics, in which the basic principles
quantum theory is supplemented and applied to the study of specific physical systems. Modern methods of research of quantum systems are proposed – the construction of integrable potentials, the integral along trajectories, and the concepts of density matrix and effective action are introduced. The course involves a transition to the consideration of free field theories, their canonical quantization, and discussion of differences quantum mechanics from quantum field theory. The purpose of the course is to consolidate the basic principles and methods of quantum theory, study the transition from quantum mechanics to quantum field theory. The course introduces the basic concepts necessary for studying the courses of the program "Mathematical physics". The course is designed as a solution to specific problems in quantum theory (see the course content). The course involves significant independent work on solving problems. I would like the results of the course to coincide with the goals. 
Vladimir Losyakov 
63 per term

MA060428  
Quantum Theory of Radiation and Quantum Optics (Term 1B4)
The main goal of the course is to study by students basic physical principles, main quantum electrodynamical (QED) phenomena and mathematical apparatus of quantum electrodynamics and quantum optics. Students must know theory and experimental data on interaction of radiatiation with matter. Particularly will be discussed: quantum theory of electromagnetic field, problem of phase in QED, coherent and squeezed states, relativistic quantum theory of electrons and positrons, Klein paradox, diagram technique,
divergences and renormalization of mass and charge of electron, Lamb shift, cavity quantum electrodynamics (including last achievements), dynamical Casimir effect, basics of united theory of electromagnetic and weak interactions etc. 
Yuri Lozovik 
61.5 per term

Options  MA060314 
Renewable Energy
The course will present a comprehensive study of modern renewable energy resources integration to power systems. Mostly focused on wind and solar power – the main contributors to renewable generation profile – the course will provide with profound technical expertise in the field of planning, grid level behavior, and devicelevel control of renewable energy sources.
With the falling prices for power electronics devices, there is an exploding grows of grid connected renewable generation all over the world. Being taken for granted by most people, these power sources have quite sophisticated control systems inside them. In this course we will uncover the complex dynamic behavior of the systems, that govern the stable and secure operation of such devices with the main power grid. Solar and wind maximum power point tracking (MPPT) techniques to extract the maximum power from the primary sources, phaselocked loop systems for tight grid connection, doubly fed induction machines for flexible power output – are all the part of the course. 
Petr Vorobev  6  MA060201  
Representations of Classical Groups and Related Topics (Term 12)
The course is focused on fundamental results of the representation theory of classical matrix groups, which find numerous applications in various domains of mathematics. Particular attention will be paid to links with algebraic combinatorics.
Tentative program: – Characters of classical groups (general linear, orthogonal, and symplectic). 
Grigori Olshanski 
31.5 per term

MA030423  
Research (Term 58)  Mikhail Skvortsov 
61.5 per term

MA060432  
Research Methodology: Computational and Data Science and Engineering (Term 23)  Maxim Fedorov 
31.5 per term

DA030102cds  
Research Methodology: Molecular Biology Seminar
Main topic of term2 seminar will be "CRISPR – the beginnings"
For each class, there will be a paper that two people will present to the rest of the class. We will go down to the details of experiments – how things were done and what do the data/figures really show, so be prepared to answer indepth questions. Presenters will start by stating the name of the paper/main authors and telling the take home message of the paper – why it is signficant, what problem it solved. Then they will proceed to the actual work. If there are methods/results mentioned in the paper that refer to prior work, you shall be prepared to answer questions about it too. The audience is supposed to read the paper being discussed beforehand and participate in discussions. To pass, one would need to present a paper at least once during the module and actively take part in discussions of other papers. One absence is allowed no questions asked. Additional absences when unexplained will be a cause for nopass grade. There will be a few home assignments. They must be submitted in time, typed–not written up–and done professionally (written in good language, be concise and free of spelling errors – consider them as part of academic writing exercises). It is gonna be fun – students tend to like the seminar and its atmosphere Dear students, Please note that the final list of participants will be selected by prof. Severinov after registration closes. 
Konstantin Severinov  3  DA030102ls  
Research Methodology: Space Center Seminar (Term 14)
The seminar will cover current topics in the space domain: latest news, discoveries. Also planned that all PhD students and some Master students will present their research. External lecturers will be invited regularly to focus on the main applications of space technologies: science, telecommunication, navigation and remote sensing. Aspects of space technologies will also be discussed: structures, software, attitude determination and control systems, on board computers, communication system power supply systems and others. The seminar will be offered in English.

Anton Ivanov 
30.75 per term

DA030102es  
Research Seminar "Advanced Materials Science" (Term 28)  Keith Stevenson 
30.5 per term

DA030302  
Research seminar "Energy Systems and Technologies" (Term 24)
This research seminar is the general meeting for faculty, researchers and master and PhD students of Energy Systems programs. The seminar takes place every week during Terms 2(6)3(7)4(8).
Master students must attend the seminar at least for one academic year but welcome to attend during two years. PhD students are welcome to attend the seminar during all years of studies but can gain no more than 6 credits in total. The seminar consists of faculty lectures, invited lectures of top scientists in their research field as well as students’ reports on their own or examined papers. To PASS the course and gain 3 credits per academic year the student must fulfill all three requirements: 1. Attendance: > 2/3 of seminars. 2. Presentation. Depending on the status: 3. Evaluation. Filling in the Online feedback form. The core of the selfstudy activity will be preparation to the talk that is comparable to project implementation (a significant part of many regular courses). The students are expected to assign at the beginning of Term 2/6 and may drop the seminar till the beginning of Term 3/7 while credits are provided in Term 4/8. 
Elena Gryazina 
31 per term

MA030386  
Research seminar "Modern Problems of Mathematical Physics" (Term 14)
Course "Modern problems of mathematical physics" is a student seminar, so participants are expected to give talks based on the modern research papers. Current topic of the seminar can vary from time to time: now it is devoted to the study of N=2 supersymmetric gauge theory and its links with random matrix models, ABJM theory, localization, complex curves, and integrable systems. Other topics that were already covered, or can be covered in the future, are: classical integrable equations, complex curves and their thetafunctions, quantum integrable models (quantummechanical and fieldtheoretical), models of statistical physics.

Pavlo Gavrylenko 
61.5 per term

DA060268  
Research seminar "Modern Problems of Theoretical Physics" (Term 14)
Research seminar "Modern Problems of Theoretical Physics" is supposed to teach students to read, understand and represent to the audience recent advances in theoretical physics. Each student is supposed 1) to choose one of recent research papers from the list composed by the instructor in the beginning of each term, 2) read it carefully, 3) present the major results of the paper to his/her colleagues during the seminar talk, 4) answer the questions from the audience about the content of the paper. The papers in the list are selected, normally, from the condensed matter theory and related fields, like: physics quantum computing, statistical physics, etc. The papers to the list are usually chosen from most competitive physics journals, like Nature Physics, Science, Physical Review Letters, Physical Review X and others.

Mikhail Feigelman, Konstantin Tikhonov 
61.5 per term

DA060319  
Research seminar "Supersymmetric Gauge Theories and Integrable Systems" (Term 12)
The course will be devoted to the study of N=2 supersymmetric gauge theories and related topics. It turns out that comparing to the N=1 theories, N=2 allows to compute much more quantities. In particular, lowenergy effective action can be described in terms of single function, prepotential. SeibergWitten solution of the N=2 theory gives explicit description of the prepotential in terms of periods of some meromorphic differentials on algebraic curves. It turns out that this description is deeply related to classical integrable systems.
During the course we will learn basics of the N=2 theories, classical solutions, holomorhy arguments, and so on, study SeibergWitten exact solution, and then its underlying integrable systems. We are also going to learn some modern developments of this topic, like Nekrasov instanton computations and AGT relation. 
Pavlo Gavrylenko, Andrey Marshakov 
63 per term

DA060382  
Reservoir Rock Characterization
The course provides both conclusive theoretical knowledge in reservoir characterization and practical skills in laboratory measurements of the rock properties. During the course the students will learn the key rock parameters, defining the reservoir geological and recoverable reserves, well design and completion, field development strategy and rates of economic production. Particular emphasis is made on the genesis and relationships of the rock properties as well as their relevance for well logging data interpretation and geological modeling.
The course includes lectures, laboratory practicums and seminars. The participants will get acquainted with every stage of reservoir rock study, starting from coring while drilling, core handling at the well site, its further processing, sampling, transportation and preparation for laboratory tests. Further the students will learn in details routing and special laboratory tests (SCAL). Finally, the students will study how to designed a laboratory program, acknowledging geology and rock properties of a reservoir. 
Alexei Tchistiakov  3  MA030346  
Robotics
The lecture course introduce you to basics knowledge of methods for robot design, simulation, and control of robotic system. Topics include robot kinematics, dynamics, control, design, simulation, motion planning, and AI. The course slightly touches the research in wearable, space and telexistence robotics. The projects in robotics done by the lecturer, such as NurseSim, iFeel_IM!, FlexTorque, NAVIgoid, TeleTA will be presented. The lecture aims at student preparation and motivation to conduct projects in Robotics, Automation, Advanced manufacturing, and Intelligent Systems.

Dzmitry Tsetserukou  6  MA060050  
Selected Topics in Energy: Physical, Chemical and Geophysical Challenges (Term 24)
The course provides an introduction to the modern topics related to fundamentals of exploration of energy resources, energy generation, storage, conversion and use. It identifies the corresponding practical challenges to be addressed at the fundamental research level and familiarizes the students with the stateoftheart approaches, methods and techniques in use in related scientific areas. The course seeks to emphasize and maintain interdisciplinary nature of the energyrelated topics, in particular, combination of micro and macroscopic approaches of geophysics, mechanics and chemistry in hydrocarbon exploration and development, relation between the physical and chemical processes of energy generation and conversion, integration of physical, chemical and mechanical approaches to perspective materials (physical and chemical synthesis, micro and macroscopic characterization, structureproperty relations, etc.) and related theoretical methodologies. These interdisciplinary links are mostly demonstrated by horizontal knowledge exchange among the students reporting and discussing practical examples from their own research field or from modern review or research publications. Topical lectures are included for further exploration of these links. The secondary aim of the course is the development of presentation skills (oral and writing), as well as scientific peerreview experience. The seminar format chosen for most activities allows students free exchange of knowledge and ideas, broader vision of their research projects and methodologies, better assessments of their own research skills and demands for further education.

Alexei Buchachenko 
62 per term

DA060106  
Spacecraft Dynamics and Control
This course surveys basic concepts and computational fundamentals of astrodynamics and then proceeds with the principles of spacecraft attitude determination and control. The emphasis throughout the course is made on solving realworld engineering problems and analyzing uptodate misions. Orbital and rotational dynamics of spacecraft are discussed and simulated under a variety of environmental conditions, along with the realistic constraints imposed by available hardware.
The first part of the course is focused on the orbital dynamics of spacecraft and discusses main principles of how the orbits of satellites or trajectories of spacecraft are formed due to environmental factors and how they are designed, when a space mission is planned. The second part of the course shows a few methods of nonlinear dynamics identification and control through the example of attitude control systems. The students will learn how the attitude control systems are modeled and designed, and what sensors, actuators and algorithms are used. 
Dmitry Pritykin  6  MA060379  
Startup Workshop  Alexey Nikolaev, Dmitry Kulish 
3  E&I  MC030025 
Statistical Mechanics and Kinetics (Term 12)
In this course we will consider a broad range of fundamental topics in statistical mechanics and physical kinetics. We will begin with a review of basic concepts of statistical mechanics and thermodynamics, and will then progress to more advanced themes. These include quantum degenerate gases, phase equilibrium and phase transitions (including Landau theory of second order phase transitions), theory of linear response and fluctuations, and treatment of nonequilibrium phenomena using the Boltzmann kinetic equation. Examples considered in class and homework assignments will focus on applications of the general formalism to physical systems. The course is intended for both experimentalists and theorists.

Anton Andreev 
63 per term

MA060339  
Statistical Natural Language Processing
This course gives introductionary insights into statistical methods that are used in natural language processing systems. The goal of this course:
= understand statistical methods for language processing in detail = feeling for language tech applications, avoiding pitfalls = ability to plan technology requirements for a language tech project = analyze and evaluate the use of NLP in applications = see the beauty of language technology, be ready to write your thesis in language tech. This is an introductory NLP course dedicated to classic algorithms based on the Jurafsky and Martin textbook. Later, we will offer also an additional course covering neural methods for NLP based on the Goldberg textbook. 
Alexander Panchenko  3  MA030131  
Stochastic Methods in Mathematical Modeling
Stochastic processes play an important role in natural sciences, computational theory as well as in sampling and synthetic data generation for machine learning. The course aims to cover basic methods of stochastic modelling, such as: MonteCarlo methods, the modelling of scalefree phenomena as well as stochastic optimisation approaches.
The first part of the course provides an introduction to the methods of description, types and generation of randomness. The main idea is to establish a firm ground for more advanced topics and to help students feel comfortable with advanced machine learning courses. A special emphasis is put on the ubiquitous scalefree and nongaussian stochastic processes also known as anomalous diffusion. Different causes of these processes will be discussed with examples such as practically important class of firstpassage problems. The second half of the course will deal with MonteCarlo algorithms, inference and learning, classical random network theory, Markov decision processes and stochastic optimal control. 
Vladimir Palyulin  6  MA060363  
Structural Analysis and Design
The Structural analysis and Design course gives students basics of strength analysis and design of typical structural members. Theoretical sections include introductions into stress and strain theories, failure criteria, elasticity theory, nonlinear material behavior and analysis of tension, compression, bending and shear structural members. Students learn finite element software Abaqus and work on development of FE models and stress analysis of structural parts taking into account nonlinear material behaviour, mechanical and thermal interactions.

Ivan Sergeichev  6  MA060067  
Structural Bioinformatics
The main goal of the Structural bioinformatics course is to introduce students to the main features of protein structures and to the explanations of the observed features.
The Structural bioinformatics course covers the following topics: In a more theoretical part of the course, we will overview (i) protein primary, secondary and tertiary structures, (ii) interactions stabilizing protein native structure (discussing the role of energy and entropy), (iii) statistical patterns observed in protein structures, (iv) protein thermodynamics, (v) protein kinetics, (vi) protein folding problem, and others. We will also discuss the design and the results of the selected experiments in the field. In a more practical part of the course, we will (i) visualize protein threedimensional structures, (ii) align protein sequences and structures, (iii) predict threedimensional protein structure from sequence, (iv) predict protein cellular localization and transmembrane topology, (v) predict the impact of a mutation on protein stability, and others. 
Dmitry Ivankov  6  MA060375  
Systems Engineering
The course introduces students to the fundamentals of systems engineering as an interdisciplinary approach and means to enable the realization of successful systems, as defined by the International Council of Systems Engineering.
The course covers the entire spectrum of the lifecycle management of a system, encompassing conceptual design, design, implementation, assemblyIntegration and test (AIT), operations and disposal of systems. Being a foundational course for the Space and Engineering Systems students of Skoltech, the course discusses many applications of systems engineering including some parts of space systems engineering . The course also discusses systems architecture principles. The Systems Engineering course follows the systems engineering Vmodel as an educational guideline. The course includes a design project that is conducted throughout the term. 
Anton Ivanov, Clement Fortin 
6  MA060023  
Technology Commercialization: Foundations for Doctoral Researchers
In knowledgebased society, more than ever before, it is imperative that inventions, scientific knowledge and technological knowledge created throughout research at universities have an impact outside university faculties and laboratories. Commercialization of research is a means to fulfill that goal. This course is designed to help PhD students to consider their research ideas and results through the lenses of opportunities that are attractive for business and investors, and to prepare them to make impact through commercial execution of those opportunities.
The course lays the foundation to undertake a robust analysis and design of opportunities for technological innovation. It helps PhD students to develop the ability to recognize, evaluate, and develop technological ideas into commercially viable product and service concepts, and build those concepts into viable business propositions. We introduce tools and frameworks to help isolate and control the factors shaping the identification, evaluation and development of commercial opportunities. During the course, students first gain practical experience in shaping technologybased opportunities (originating from problems found in engineering and scientific education) and in identifying marketbased opportunities (from social, economic and environmental contexts). Students are then challenged to employ that same commercialization framework to reflect on and examine ideas and scientific results from their own doctoral research, link these with appropriate marketbased opportunities, and identify one or more pathways to create practical impact from their ideas. The material covered is research and theorybased but the course is practiceoriented with much of the term spent on shaping technologybased opportunities. A central objective of this subject is to equip students with an understanding of the main issues involved in the commercialization of technological advances at both strategic and operational levels. 
Zeljko Tekic  6  E&I  DC060002 
Theoretical Methods of Deep Learning
Deep Learning (DL) is a highly promising and popular applied science that, at present, is poorly understood theoretically. We know that neural networks work well, but cannot fully explain why. Nevertheless, in the last few years, there has been a rapid growth of publications that shed light on the new mathematics underlying DL, and we see now many interesting connections between DL and other fields such as approximation theory, random matrix theory, and statistical physics. This course aims to introduce students to these cuttingedge developments.

Dmitry Yarotsky  3  MA030327  
Theory of Phase Transitions (Term 12)
The role of longrange thermal fluctuations in the condensed matter
physics is considered. We give a theory of the second order transitions starting from the Landau expansion in the order parameter. As an introduction we consider the mean field theory, then we take into account fluctuations the role of which can be examined in the framework of the perturbation theory and the socalled renormgroup formalism. The peculiarities of a weak crystallization transition where fluctuations qualitatively change the nature of the phase transition in comparison with the mean field picture are treated on the same diagrammatic language. The theoretical approach based on the Landau expansion is utilized to examine thermal fluctuation effects far from phase transition points. We consider the longscale properties of smectics where fluctuations destroy the longrange order. The smectics are treated in the framework of the renormgroup approach. The same renormgroup technique is developed also for twodimensional ferromagnets where the effective coupling constant increases with increasing scale what drastically change longscale properties of the system. Longrange fluctuations are also relevant for membranes which are twodimensional objects immersed into a threedimensional fluid. Elastic modules of a membrane are logarithmically renormalized, the renormalization law can be found by using renormgroup methods. Of special interest is BerezinskiiKosterlitzThouless phase transition in superfluid, crystal or hexatic films which is related to appearing free point defects (vortices, dislocations or disclinations). The problem can be mapped into sineGordon model and then examined by renormgroup methods. We present some facts concerning critical dynamics and the socalled KPZ (KardarParisiZhang) problem. Then we consider peculiarities of the 2d hydrodynamics and passive scalar. 
Vladimir Lebedev 
63 per term

MA060138  
Thermal Petrophysics and Geothermy  Yuri Popov  6  DA060295  
Transport in Mesoscopic Systems
The course aims to provide introduction to a modern direction of the solidstate physics, devoted to studying charge transport (charge currents) in mesoscopic structures. Mesoscopic structures are intermediate between micro and macroscopic systems; in our context, this name refers to systems with many electron in which mechanics (in particular, quantum mechanics) of single electrons is still important. The course consists of two parts, devoted to normal (i.e., nonsuperconducting) and superconducting systems. A number of these systems form a basis for nanoelectronics devices. The course assumes participation of students interested in both experimental and theoretical aspects of mesoscopic research.

Yakov Fominov  6  MA060217 
Course Title  Lead Instructors  ECTS Credits  Stream  Course Code 

Academic Communication: Preparatory English for Phd Exam (Term 34)
Efficient professional communication is the key to Academic success. The course is designed for PhD students who want to maximize their academic potential by boosting their ability to write research papers, present in front of multidisciplinary audiences, participate in scholarly discussions and engage in other forms of academic communication.
The main goal of the course is to enable PhD students to produce clear, correct, concise and coherent texts acceptable for the international professional community. The course is designed for a multidisciplinary audience. The course serves as a preparation for the qualification language exam, which is a prerequisite for the Thesis defense. 
Elizaveta Tikhomirova 
31.5 per term

DE030029  
Academic Writing Essentials (Term 34)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030002ls 
Academic Writing Essentials (Term 34)
Academic writing skills are necessary for effective research, innovation, and educational activities in a multinational setting. The aim of the course is to provide guidelines and strategies for writing academic texts, focusing on relevant aspects of grammar, vocabulary, and style. The course includes analysis and practice of various forms of scientific and technical writing, and builds writing skills from sentences to paragraph structure, from summary to abstract, and lays the foundations for writing scientific papers and Master Thesis.
Modern science is, for most purposes, a collective collaborative effort, so the course is designed to promote individual and group responsibility by providing mutually related and timedependent tasks, such as peer review. The course is writingintensive with ample opportunity to practice editing and peerreviewing. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030002 
Advanced Drilling and Completion Technologies
Course will cover basic and advanced drilling and completion technologies during well planning and execution. Planning phase includes basics of well design: selection of trajectory, casing, drilling fluid, drilling string, bottom hole assembly (drilling bits, rotary steerable systems, mud motors, measured while drilling and logging while drilling tools), cement, lower completion and upper completion, wellheads, xmass tree, drilling rig, etc. Execution phase covers techniques of directional drilling, hole cleaning, casing running, cementing operation, completion running and emergency situations prevention and recovery while drilling (well control, stuck pipe, etc.). The course will cover basics of the offshore drilling and completion.

Kirill Bogachev  3  MA030347  
Advanced Molecular Biology Laboratory Practice
This course offers students the opportunity to work individually on laboratory projects assigned by the course instructor. During the term students are expected to have at least one entire working day in the lab, although additional days may be required. Final grades are determined by the students' final presentations, which describe their project/goals along with the results/progress accomplished. Participation in the course requires approval from the students' own advisors, as well as the instructors of the course

Konstantin Severinov  6  DA060046  
Advanced PLM techniques: Digital Design and Optimization
This course is dedicated to the endtoend design methodology, based on the PLM approach. During the course students will develop small unmanned aerial vehicle with deployable wings.
The design includes: concept development, conceptual design, systems engineering, 3D physical simulation (CFD and FEM), parametric and topology optimization, final solid design. Educational process is focused on teamwork in this course. Siemens Teamcenter PLM platform is used as to provide interaction within students workgroup. The course provides students with a theoretical and practical basis for implementing projects devoted to the design of complex technical systems, such as unmanned aerial vehicles. 
Ighor Uzhinsky, Sergei Nikolaev 
6  MA060252  
Advanced Statistical Methods
This course introduces the main notions, approaches, and methods of nonparametric statistics. The main topics include smoothing and regularization, model selection and parameter tuning, structural inference, efficiency and rate efficiency, local and sieve parametric approaches. The study is mainly limited to regression and density models. The topics of this course form an essential basis for working with complex data structures using modern statistical tools.
Course structure: lectures, seminars, exam. 
Vladimir Spokoiny  3  MA030132  
Applied Geomechanics  Sergey Stanchits  6  DA060190  
Basic Molecular Biology Techniques
The purpose of this course is to provide students with the opportunity to obtain and develop the basic set of skills needed to be successful in a molecular biology laboratory. The course consists of handson laboratory work, as well as lectures from course instructors. Students without any significant background in the biological sciences should be advised that additional reading outside of the scheduled classes may be necessary to maximize classroom success (instructors are happy to provide resources at the students’ request).

Svetlana Dubiley  6  MA060022  
Biostatistics
This introductory course to statistics and probability theory is modeled as an extension of a traditional university Statistics course and Advanced Placement Course in Statistics to a broader spectrum of topics, while keeping the spirit of quantitative discourse applied to reallife problems. The material is offered in 5 consecutive modules (see Course Outline below), each containing a lecture, a discussion section, and a practicum. For practical exercises we use R programming language and RStudio software. However, this course is focused on statistics rather than R; therefore, each practicum is designed with the purpose to demonstrate and reinforce understanding of concepts introduced in the lecture rather than to provide a training in R.

Dmitri Pervouchine  6  MA060036  
Business Communication
Business Communication is an intensive hands on, practical course, designed to provide Skoltech students with the set of skills needed to effectively communicate with others – their classmates, working teams, professors and any audiences inside and outside of Skoltech. The course learning outcomes correspond directly with the Group 3 of Skoltech learning outcomes – “Relating to Others – Communication and Collaboration”. The course will show students the secrets and technologies to becoming confident when speaking in public – developing the skills they will be able to use throughout their career and their life. In a highly interactive, informative and supportive manner through inclass activities, games and simulations the course will enable students to: Speak with confidence and overcome their nervousness; Establish rapport with any audience; Present their message in a clear, concise, and engaging manner; Successfully manage impression they make onto audience; Create—and repurpose—presentations quickly and efficiently; Make successful and memorable pitch; Sharpen the story they want to tell; Use confidently body language and movement, strengthening their speech; Respond to questions and comments without getting flustered; Gain people’s attention, respect, and cooperation.

Maxim Kiselev  3  E&I  MC030014 
Carbon Nanomaterials  Albert Nasibulin  6  DA060044  
Composite Materials and Structures
This course aims to provide knowledge about manufacturing, properties, and contemporary problems in composite materials. The emphasis is on the practical applications, theoretical background, and the use of composite materials in industry. The course cuts across several domains, covering mechanics of materials, design, manufacturing, and in service issues:
• Introduction: What is a composite? Classification. Metals vs composites, advantages and disadvantages. Applications in industry. Participants will learn fundamentals of these areas through active participation in teamwork. The course will provide practical knowledge on applications of composite materials in aerospace and mechanical engineering. 
Sergey Abaimov  6  MA060241  
Computational Materials Science Seminar (Term 28)  Dmitry Aksenov 
30.5 per term

MA030430  
Condensed Matter Spectroscopy and Physics of Nanostructures (Term 1B4)
This course presents a modern introduction to the field of optical phenomena in condensed matter and nanostructures. The first part of the course starts from the classical and quantum theory of electromagnetic response, and basics of the condensed matter spectroscopy. Then the major research directions in the modern condensed matter spectroscopy are considered, such as spectroscopy of graphene, topological materials, and twodimensional transition metal dichalcogenides. The second part of the course is focused on specific optical phenomena in semiconductors, heterostructures, nanostructures and interfaces, such as surface plasmons and polaritons, excitons, spinorbit coupling effects, Raman scattering and color centers.

Anatoly Mal’shukov 
61.5 per term

Options  MA060313 
Continuum Mechanics (Term 23)  Robert Nigmatulin 
63 per term

DA060181  
Control Systems Engineering
The course focuses on dynamic systems, and their control. Such systems evolve with time and have inputs, disturbance, and outputs. One can find examples of dynamic systems in everyday life, for examples, automobiles, aircrafts, cranes, electrical circuits, fluid flow.
You will analyze the response of these systems to input. Students will learn how to control system through feedback to ensure desirable dynamic properties (performance, stability). The practice will include work with an industrial, a humanoid, a mobile, and a telepresence robot. 
Dzmitry Tsetserukou  6  MA060083  
Digital Certification of Composite Structures
The course is introduced methods of conformity assessment of composite structures mostly related to civil engineering and infrastructure. These methods are based on the multi scale testing and simulation of the structures. The test standards are discussed and utilize within laboratory practice in order to obtain the material properties required for identification of constitutive material models and failure criteria. The general approaches to development and verification of material models and failure criteria are presented focusing to finite element implementation. The virtual tests of simple composite structure are performed utilizing these material models and criteria identified by the standard test results. Finally, the obtained digital model of the structure is validated by the appropriate fullscale test data. The validated digital model is used for analysis of structural behavior aiming to confirm the safety and functionality of the structure according to regulations. Therefore, the total chain of tests and simulations are performed for conformity assessment and certification of the given simple composite structure. As the introduction to the certification the general conformity assessment procedures utilized into airspace industry are discussed focusing to composite structures.

Ivan Sergeichev  3  MA030357  
Energy Colloquium
The Energy Colloquium educates the audience in the presentday research and applications within the broader field of Energy Science and Technology. The Colloquium consists of a series of presentations by invited academic and industry speakers. The presentations target a nonspecialist audience.
All Master and Ph.D. students within the Energy Program are encouraged to attend the Energy Colloquium during the entire period of their studies. Students can earn 1 credit, if he/she participates in the Energy Colloquium over the course of any 2 terms of the academic year. Students who passed one round can make next (for credit) over the course of their subsequent studies. 
Alexei Buchachenko  1  Extra  MF010092 
English. Candidate Examinations
This is a blended metacourse for the English Qualification Exam needed for the Russian PhD Degree. The Exam is designed as a multidisciplinary conference where the participants present results of their PhD research and follows the general principles of conference materials submission, peer review, resubmission, presentation, and discussion.
The goal of the Exam is Academic Communication, so the participants should demonstrate the ability to present their research results in front of a multidisciplinary audience and deliver the key ideas in good Academic English in terms of vocabulary, grammar and style. Preexam/ preconference activities, such as material submissions and peer reviews, last of three weeks and take place fully online. They include: Project proposal V1+ 2 Peer Reviews; a 2minute video annotation V1 + peer review; and a stack of presentation slides V1+ peer review. Version 2 of the Proposal, video annotation and the slides should be improved using the comments of the Instructor and the peers. Depending on the applicable regulations related to COVID19, on the Examination day students make their presentations and participate in the discussion in person or via an online platform in front of the Examination Committee and a group of peers. Failure to submit an assignment by the due date may result in the loss of the grade. The participants will practice a variety of academic skills: – Planning and designing a wellstructured and balanced presentation The grade is counted towards the PhD Qualification. 
Elizaveta Tikhomirova  3  DE030003  
Fabrication Technology of Nanodevices  Vladimir Antonov  6  MA060311  
Foundations of Multiscale Modeling: Kinetics
The course is devoted to fundamental principles of modelling of kinetic processes at different time and space scales. The basic concepts are introduced, along with the theoretical and numerical techniques, which application to practical problems is illustrated. The course starts with the description of molecular kinetics in fluids, colloidal and polymer solutions; applications for molecular machines and nanorobotics is considered. Langevin and FokkerPlanck equations are introduced, supplemented with the theoretical and numerical tools of their solution.
Next, the Boltzmann kinetic equation is analyzed. An application of the fundamental theoretical and numerical techniques, such as Grad and ChapmanEnskog methods, Lattice Boltzmann and Direct Simulation Monte Carlo is illustrated. Derivation of transport coefficients and hydrodynamics equations, including these for dissipative fluids, is given. GreenKubo relations as an alternative method for practical computation of transport coefficients is presented and compared with other methods. Based on the Boltzmann equation, the theory of aggregationfragmentation kinetics is developed, leading to the generalized Smoluchowski equations. The basic concepts like Scaling, Generation functions, etc. are introduced for theoretical analysis and Gillespe algorithm and fast solvers for practical computations. In the rest of the course the above theoretical and numerical techniques are illustrated for the following applications: Surface growth, Phase transition kinetics, Random sequential adsorption, Nucleation & Growth and Nanotribology. Theory of Active Matter, Traffic Models, Sociodynamics and Complex Networks dynamics are also considered. The knowledge of undergraduate mathematics – the basics of calculus, linear algebra and probability theory, as well as reasonable skills in Matlab and Python are needed. A familiarity with the basic open source software is desirable. 
Nikolay Brilliantov  6  MA060326  
Functional Methods in the Theory of Disordered Systems (Term 34)
The course provides an extensive overview of contemporary functional methods in the theory of disordered systems. Starting from the theory of random matrices, it covers various aspects of electron motion in disordered media. The concept of the nonlinear supersymmetric sigma model is introduced and used as a unique language to describe such phenomena as energy level statistics, weak localization, renormalization group analysis, nonperturbative solution of the localization problem in quantum wires. Finally, functional integral method is used to address electronelectron interaction in disordered metals and nonequilibrium phenomena in quantum dots.

Mikhail Skvortsov 
63 per term

MA060262  
Fundamentals in Methodology of Scientific Research (Term 34)
The course can be considered as a tutorial for MS and PhD students performing R&D projects within their educational tracks (e.g. while preparing thesis) and extracurricular activities focused on building scientific or entrepreneur career. In the frame of the course, we will explore the most efficient strategies for performing R&D projects starting from planning the research program and ending up with the dissemination and application of the obtained results, e.g. by filing patents, licensing or making startups. Using a set of examples, we will discuss how to address the most common challenges in scientific research and present the obtained results in a proper way. In particular, students will be actively involved in practical trainings learning how to analyze a potential impact of their results, prepare conference presentations, scientific publications and research projects. This course is designed mainly for MS and PhD students involved in experimental studies in interdisciplinary fields, mainly at the interface of physics and chemistry, aiming to address relevant challenges of modern materials science.

Pavel Troshin 
63 per term

MA060342  
Fundamentals of Additive Technologies
Additive manufacturing (AM), also called 3D printing, has become an extremely promising technology nowadays. Unlike traditional manufacturing processes such as welding, milling and melting that involve multistage processing and treatments, AM allows to create products with a new level of performance and shapes.
Moreover, this technique allows to produce prototypes rapidly and leads to reducing costs and risks. Another crucial advantage of the technology is the unprecedented design flexibility that let us create the samples of high quality based on different materials such as metals, alloys, ceramics, polymers, composite materials etc. The main goal of this course is to represent the fundamental basis of different additive technologies to the students. In this course, a wide range of questions will be addressed, beginning from the process of chain and designing the structures up to various 3D printing technologies, materials and process parameters, benefits and drawbacks of AM approaches will be considered. During laboratory class, we will get acquainted with the additive technologies on various printing machines. Students will be able to create their own models, print them in metals, ceramics and polymers, and also analyze the properties of the final samples. During this course, a complete cycle of production of samples using various 3D printing techniques will be explored both theoretically and practically. 
Igor Shishkovsky  6  MA060243  
Fundamentals of Optics of Nanoscale Systems (Term 1B4)
The course focuses on the general concepts and experimental developments in the rapidly evolving field of the modern physics of nanosized systems. It covers a broad spectrum of optics on the nanometer scale, ranging from fundamental nanoscience to nanotechnology applications. Topics covered include: foundations of lightmatter interaction at nanoscale, concepts of nearfield and quantum confinement, nanoplasmonics, optical emission of pointed nanoparticles (fluorescent molecules, quantum dots, plasmonic nanoparticles et al). Various experimental methods that used in nanooptics and nanoscience, including nearfield and farfield optical microscopy of subdiffraction spatial resolution, are presented. Nanophotonic devices, photonic crystals, spasers, singlephoton sources, nanosensors are discussed. Seminars assume the discussion of papers presenting a physical basis for nanoscale optical phenomena, as well as the papers describing the last achievements in the area.

Yuri Vainer 
61.5 per term

Options  MA060437 
Fundamentals of Remote Sensing This course introduces students to the first principles and methods of the observation of Earth surface, monitoring of Earth atmosphere and detection of different kind of radiation coming from Space. The course will cover wide range of the satellites, aircraft, rockets and balloon based techniques designed for environmental monitoring, meteorology, map making etc. Goals of the course include: a comprehensive knowledge of the principles and approaches to the creation and operation of remote sensing systems; acquisition of analysis skills of modern ERS programs; practical application of acquired knowledge and Course will also include a module on geomatics, i.e. platforms, sensors and methodologies related to the collection, processing, analysis and interpretation of (2D/3D) data related to Earth's surface. This includes platforms like satellite or drones, sensors like LiDAR or airborne cameras and techniques like photogrammetry, laser scanning, geodesy, topography, etc. Major learning outcomes include operational principles and design of different sensors used in remote sensing of the Earth, practical skills to design an experiment in remote sensing with applications to a practical business need. 
Vladimir Gershenzon  6  MA060186  
Gas Recovery and Methane Hydrates
Natural gases characterization of the gas and gascondensate fields. Traditional and nonconventional gas resources. Overview of technological complications (flow assurance) in gas production at different stages of field development.
Phase diagrams of hydrocarbon systems including water. General characteristics of phase transformations during reservoir development. A moisture content of natural gas. Gas hydrates: basic physical and chemical properties. Twophase and threephase equilibria. Gas hydrates as a technological complication in gas production. Thermodynamic (methanol and MEG) and lowdosage (kinetic and antiagglomerant) inhibitors. Permafrost at northern gas fields: general characteristic, ice content, thermophysical and mechanical properties of frozen and thawed rocks. Wells and well clusters. Thawing and reverse freezing of rocks around the producing well. Simulation of the thermal interaction of well and permafrost rocks. Thermal regime of the operating well. Gas gathering systems. Technological complications in the operation of infield systems. Gas hydrate control. Gas gathering systems at the late stages of field development (water accumulations, ice formation, sand, scales). The main technological processes of gas treatment in field conditions (general overview). Dehydration of lean gases. Adsorption method of dehydration. Adsorbents and their choice. Technological schemes of adsorption dehydration. Absorption method of dehydration.Glycols as absorbents.Technological schemes of absorption dehydration. Lowtemperature processes of gas treatment at gascondensate fields. Isoenthalpic and isoentropic processes. The lowtemperature separation technology and its modifications (application of ejectors, turboexpanders, gasdynamic separators and vortex tubes in process diagrams). Application of thermodynamic inhibitors (methanol, MEG) for hydrate control. Promising lowtemperature technological schemes for gas processing at field conditions. 
Vladimir Istomin  3  MA030291  
Gauge Fields and Complex Geometry (Term 34)
1. Selfduality equations, Bogomolny equations.
2. Relation to holomorphic bundles. 3. Relation to holomorphic bundles on twistor space. 4. Conformal symmetry and complex geometry in twistor space. 5. Elements of superfield formulation of SUSY field theories. 6. Chirality type constraints and complex geometry. 7. Some examples of superfield theories which require complex geometry. 8. BPS conditions in SUSY theories and complex geometry. 9. Elements of Hitchin's integrable systems and related complex geometry. 
Alexey Rosly 
63 per term

MA060178  
Geometric Computer Vision
Geometry plays an extremely important role in many computer vision algorithms as certain kinds of geometric transformations (e.g., projective) form the basis of imaging, estimation, and reconstruction. This course focuses on obtaining 3D scene geometry from both images and depth sensory data. We will cover principles of projective geometry and camera models, monocular, stereo, and multiview vision as well as the fundamentals of depth sensing and digital geometry processing from rangeimages. The course only slightly relies on previous knowledge of deep learning, yet features some deep architectures for 3D data processing. Most of the material, however, is devoted to more principled topics of computer vision such as camera calibration, stereomatching, registration, reconstruction, among others.

Alexey Artemov  3  MA030362  
Information and Coding Theory
The aim of the course is to explain basic ideas and results of information and coding theory, some of which has been used for rather long time in data science, in particular various entropy inequalities, and some emerged just very recently, for instance, usage of errorcorrecting codes for improvements of kmeans method for clustering. The course is divided into two parts: introduction to information theory and elements of modern coding theory. In the first part, we consider the measure of information, mutual information, entropy, evaluation of channel capacity for single user and multiuser channels. In the second part, we consider foundations of coding theory such as block codes, linear codes, bounds on the code’s parameters and the most popular algebraic coding methods (Hamming, ReedMuller, BCH and ReedSolomon codes). Then we consider modern coding techniques, i.e. iterative decoding systems and graphical models to represent them. Iterative techniques have revolutionized the theory and practice of coding and have been applied in numerous communications standards. We discuss lowdensity paritycheck (LDPC) codes, factor graphs and SumProduct decoding algorithm.

Alexey Frolov  6  MA060122  
Innovation and Intellectual Property Studies Doctoral Seminar (Term 25)  Kelvin Willoughby 
61.5 per term

E&I  DC060009 
Instrumental Analysis in Molecular Biology
During this course you will get principles of main instrumental methods that are used today in molecular biology both in academia and industry. The aim of this course is to provide knowledge of modern methods for master students with minimal background in the field of molecular biology. As a result students will understand general principles of the methods used in the biomedical research and development. By focusing on examples of the biomolecule purification and purity confirmation the idea of accurate studies will be explained. The course will provide a comprehensive summary of the major methods used nowadays in the field, except microsopy. Current trends will be reviewed, along with a discussion of methods application for common tasks. Some attention will be paid to minituarization of analytical devices for the use as POC (pointofcare).
This course includes a practical part where students will be able to purify RNA and protein samples from mouse liver and analyze them by UVspectroscopy, RTqPCR, and western blot. 
Timofei Zatsepin  6  MA060250  
Intellectual Property, Technological Innovation and Entrepreneurship
Intellectual property (IP) is a critically important aspect of technological innovation and a key factor in the management of technologyintensive enterprises. Basic knowledge of intellectual property principles and practices is increasingly important for university researchers, and expertise in the management of intellectual property is a key skill set of technology leaders in both established corporations and entrepreneurial ventures.
Intellectual property affects not only technology commercialization strategy but also the direction of scientific research itself. University research groups increasingly compete with each other for scientific reputation and access to resources on the basis of their ability to obtain patent protection for the practical applications of their research; but also on the basis of their ability to plot research pathways to maneuver around the “proprietary territory” of other research groups. Skill in using IP data bases, and associated analytical tools, can empower university scientific teams to craft more powerful research strategies. This course will survey basic concepts of intellectual property and provide an introduction to a variety of types of intellectual property and IPrelated rights, such as patents, copyright, trade secrets, trademarks, design rights, database rights, domain names, and demarcations of origin. The classroom sessions will include lively discussions of case studies of the management of IP and the resolution of IPrelated problems in the process of technology commercialization. Each student will conduct an analysis of intellectual property issues related to his or her own Ph.D. research topic. Use will be made of special IP data and IP analytics tools. 
Kelvin Willoughby  6  E&I  DC060006 
Introduction to Digital Agro
The agriculture and food sector is facing multiple challenges. With the global population projected to grow from 7.6 billion in 2018 to over 9.6 billion in 2050 there will be a significant increase in the demand for food. At the same time, the availability of natural resources such as fresh water and productive arable land is becoming increasingly
constrained. This will require an urgent transformation of the current agrifood system. Digital innovations and technologies may be part of the solution. The socalled ‘Fourth Industrial Revolution’ (Industry 4.0) is seeing several sectors rapidly transformed by ‘disruptive’ digital technologies such as Internet of Things, Artificial Intelligence and Computer Vision. This course will be focused on several milestone problems for Russian Agrifood sector, like: Students will try to improve and solve this issue on a real cases and real BigData. 
Maria Pukalchik  3  MA030359  
Introduction to Digital Pharma
Modern pharma undergoes digital transformation. AI and other ‘digital’ technologies are actively applied in drug discovery and development to make the whole process less time consuming and more costeffective.
The course will cover all aspects of drug design and development where digital technologies are being implemented: ● Identification of drug target and its druggability assessment (genome mining), virtual high throughput screening. ● Computeraided drug design, combinatorial chemistry, exploration of chemical space. AI as a tool for chemical synthesis of new druglike molecules. ● Informatics approaches in prediction of the absorption, distribution, metabolism, elimination and toxicity (ADMET) of drug molecules. ● Informatics approaches in preart and freedom to operate analysis. ● Machine learning in clinical trials and drug repurposing. ● Formulation Development ● AI and Personalized Medicine. 2 invited lectures/seminars of companies developing informatics solutions for research and development of new medicines are planned. On site visit to ChemRar HighTech Center. At the end of the course students will know the whole pipeline of drug design and development in the pharmaceutical industry. As in general this field is dynamic with changes across R&D, clinical trials, manufacturing and regulatory processes, the AI is either already applied or will be introduced in the future. The students will get hands on experience in several particular areas of drug design with specific drug target/s. The visit to the hightech center will demonstrate how this business works in real life. 
Natalia Strushkevich  6  MA060418  
Introduction to Quantum Theory (Term 34)
One of the most striking breakthrough of the XX century is the creation of the entirely new area of physics named quantum physics. It emerged that the whole world around us obeys the laws of quantum mechanics, while the laws of classical physics that we are familiar with (such as, for example, Newton's equations) describe only macroscopic objects and can be obtained in limiting case. After that a lot of phenomena in different areas of physics found their explanation. Also quantum mechanics had a very significant impact on the development of mathematics and mathematical physics. Today quantum mechanics is one of the keystone parts of theoretical and mathematical physics.

Vladimir Losyakov 
63 per term

MA060332  
IoT: Launching New Products & Startups  Alexey Nikolaev  6  E&I  MC060026 
Laser Physics
The purpose of the course is to provide a solid background in the laser physics with strong emphasis on lasers for applications. The course will form a basis for the more advance courses in optics (Telecommunications by prof. Kueppers, Experimental optics by prof. Sakelaris). Lectures cover various aspects of modern laser physics including laser dynamics; ultrafast lasers; Ti:Sapphire, fiber and semiconductor lasers; wavelength conversion and supercontinuum generation. Course will be focusing on a practical skills. During the lectures we will make a lot of problem solving and estimations. On practical seminars we will assemble our own femtosecond fiber laser and measure its emission properties.

Yuriy Gladush  6  MA030143  
Laser Spectroscopy (Term 1B4)
Spectroscopy is a science of studies of the quantum objects using the light. Before the laser era, its methods were limited to the spectroscopies of emission, absorption, and Raman scattering. The subject of the present course is not so much an improving, using the lasers, performance of the classical approaches (although this also is mentioned) but rather learning the new (more than a dozen) methods that have become possible only due to the appearance of the lasers. The course provides knowledge of the fundamental processes in spectroscopy as well as the methods allowing one to solve the problems that require (i) ultrahigh sensitivity, (ii) ultrahigh selectivity, (iii) ultrahigh spectral resolution, and (iv) ultrahigh temporal resolution. As an elective, the effects of quantum interference are considered such as coherent population trapping, the Autler–Townes effect, electromagnetically induced transparency, lasing without inversion, and more.

Alexander Makarov, Alexey Melnikov 
61.5 per term

Options  MA060212 
MIMO Systems in Wireless Communication
This course provides an overview of modern spatial processing techniques in wireless communication systems, and shows technological aspects of massiveMIMO systems. In addition, it will be studied 3GPP standard evolution to feel requirements of high precision massiveMIMO systems from channel acquisition accuracy to algorithm robustness in case of different error influence.
We will start from basic principles of wireless communication systems; will study Shannon’s capacity, and its redefinition in terms of independent and correlated spatial channels, then move to spacetime coding, spatial filters, channel acquisition techniques in 4G and 5G NR systems. Final part of the course will be denoted to specifics of radio resource management in massiveMIMO systems. After this course, the students have to be familiar with the main principles of MIMO systems in wireless communication, understand advantages of spatial domain usage, and feel the main challenges in system level and computational aspects. 
Vladimir Lyashev  3  MA030412  
Machine Learning
The course is a general introduction to machine learning (ML) and its applications. It covers fundamental modern topics in ML, and describes the most important theoretical basis and tools necessary to investigate properties of algorithms and justify their usage. It also provides important aspects of the algorithms’ applications, illustrated using realworld problems. The course starts with an overview of canonical ML applications and problems, learning scenarios, etc. Next, we discuss in depth fundamental ML algorithms for classification, regression, clustering, etc., their properties as well as their practical applications. The last part of the course is devoted to advanced ML topics such as Gaussian processes, neural networks, active learning. Within practical sections, we show how to use the methods above to crack various realworld problems. Home assignments include application of existing algorithms to solve applied industrial problems, development of modifications of ML algorithms, as well as some theoretical exercises. The students are assumed to be familiar with basic concepts in linear algebra, probability and real analysis.

Evgeny Burnaev  6  MA060018  
Master Your Thesis in English (Term 78)
The key to efficient professional communication is the ability to convey ideas clearly, coherently and correctly both orally and in writing.
The Course offers concise and practical guidelines for writing and defending a Master Thesis at Skoltech. The course focuses on the main parts of the Thesis in terms of structure, vocabulary and grammar, and their transformations for a presentation with slides. Students will develop a conscious approach to own writing and presentations through thorough analyses of the best authentic examples combined with intensive writing and editing practice. The ‘processforproduct’ approach teaches the students to write – use (peer) reviewer’s advice – revise/edit – repeat, and creates linguistic awareness needed to avoid the typical pitfalls. The Course is offered in two modules which gradually build on the necessary writing and presentation skills. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030003 
Master Your Thesis in English 1 (Term 78)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030003ls 
Material Structure Characterization Methods  Artem Abakumov  6  DA060116  
Modern Dynamical Systems (Term 34)
Dynamical systems in our course will be presented mainly not as an independent branch of mathematics but as a very powerful tool that can be applied in geometry, topology, probability, analysis, number theory and physics. We consciously decided to sacrifice some classical chapters of ergodic theory and to introduce the most important dynamical notions and ideas in the geometric and topological context already intuitively familiar to our audience. As a compensation, we will show applications of dynamics to important problems in other mathematical disciplines. We hope to arrive at the end of the course to the most recent advances in dynamics and geometry and to present (at least informally) some of results of A. Avila, A. Eskin, M. Kontsevich, M. Mirzakhani, G. Margulis.
In accordance with this strategy, the course comprises several blocks closely related to each other. The first three of them (including very short introduction) are mainly mandatory. The decision, which of the topics listed below these three blocks would depend on the background and interests of the audience. 
Alexandra Skripchenko, Sergey Lando 
63 per term

MA060257  
Molecular Biology of Sensory Systems
Sensory systems – vision, olfactory, taste, etc. – determines abilities of animals to detect environmental information and react immediately. The capabilities of sensory systems are striking in their sensitivity, specificity and wide adaptability. The course describes cellular and molecular mechanisms of reception of various environmental factors by animals. Receptor proteins and downstream cascades are considered in detail. Besides fundamental problems, related medical issues (disorders, existing and perspective therapies) and biotechnological applications (opto, thermo, chemogenetics) are discussed.

Konstantin Lukyanov  3  MA030376  
Molecular Neurobiology (Term 34)  Philipp Khaitovich 
63 per term

MA060397  
Next Generation Sequencing – Experimental Protocols and Data Analysis
Next generation sequencing is a group of methods that allow simultaneous sequencing of many thousands of DNA fragments without their physical separation by cloning. In the last 15 years it revolutionized many fields of biology: genetics, evolutionary biology, microbiology, anthropology. It have also many practical applications, especially in biomedicine. However NGS and corresponding bioinformatics methods are sometimes used in a black box regime, without understanding its logic, the area of applicability and limitations. This course will provide a comprehensive survey of both experimental aspects of NGS and of bioinformatics analysis of the data. We will also discuss the current trends in the development of sequencing technologies and their applications. The practical part of the course will offer a handson experience of a genomic project, starting from the experiment design, followed by preparation of DNA and RNA samples, sequencing, de novo genome assembly, annotation and analysis of differential expression.

Maria Logacheva  3  MA030396  
NonEquilibrium Processes in Energy Conversion
Classical thermodynamics is useful to describe equilibrium states, while nonequilibrium states and irreversibility characterize real physical processes. If one is interested in actual processes at work during energy conversion, a classical thermodynamic description of equilibrium states is insufficient as it yields very incomplete information on the processes. Irreversible thermodynamics accounts for the rates of physical processes, and provides relationships between "measurable quantities" such as transport coefficients. This graduate course, which constitutes the natural continuation of the course Energy Systems Physics & Engineering, provides the students with basic knowledge of outofequilibrium and finitetime thermodynamics, which describe irreversible processes that routinely take place in physical systems and permits a fine understanding of the processes ensuring energy conversion. Thermoelectric generators serve as the main example to illustrate in a simple fashion the outofequilibrium formalism, and other systems such as, e.g., solar cells are studied.
Essential notions which are taught include: Onsager’s approach to linear nonequilibrium thermodynamics; coupled transport theory; Boltzmann equation; thermal conductivity; electrical conductivity; electrochemical potential in solidstate systems; forceflux formalism and its application to thermoelectric systems; device optimization modelling accounting for dissipative coupling to heat reservoirs; solar energy conversion. The course is organized around the learning of essential concepts and an awareness development of current energy technologies. It is based both on "teaching with lecture" and "teaching with discussions" methods. In addition to home assignments and project, students will solve problems during tutorials and discuss their solutions. 
Henni Ouerdane  6  MA060200  
Numerical Methods in Engineering and Science
The course is intended to provide the understanding and working knowledge of numerical methods used for modeling and simulation of complex phenomena described by differential equations, focusing on fundamentals of the methods. The following topics are covered: finitedifference approximation of derivatives; interpolation; integration; steady state boundary value problems; local and global errors; stability, consistency, and convergence; matrix equations and iterative methods; initial value problems for ordinary differential equations; RungeKutta methods; multistep methods; absolute stability; stiff ODE; parabolic problems; method of lines; von Neumann analysis; hyperbolic problems; upwind methods; CourantFriedrichsLevy condition; hyperbolic systems; dissipation and dispersion; operator splitting; introduction to spectral approximation.
The course involves handson experience with programming (in Matlab or Python) and solving problems on computers. Solid knowledge of undergraduate mathematics including basic understanding of the theory of ordinary and partial differential equations of physics and engineering as well as basic programming skills are required. 
Aslan Kasimov  6  MA060239  
Numerical Modeling
Many scientific models are formulated in terms of differential or integral equations and describe continuous quantities, such as the distribution of velocity of a fluid in a space outside an aircraft wing, distribution of stress in a solid body, price of a stock as a function of time, etc. In order to use these models in a computer simulation, the models must be discretized. The course covers a representative selection of methods of discretization of differential and integral equations. The emphasis of the course is on practical aspects of using discretization methods: intuitive understanding and formal derivation of accuracy of different methods, modelling, testing and optimizing real mechanical systems, and solving applicationsinformed practical problems.

Alexander Shapeev  6  MA060005  
OneDimensional Quantum Systems (Term 34)
In the framework of the course, quantum systems (fieldtheoretic and discrete) in one spacial dimension, and some their classical statistical mechanics counterparts are discussed. The scope of systems includes sineGordon and Thirring model, O(n) sigma model, Heisenberg chain and sixvertex model, Kondo problem. We consider several techniques to obtain exact results for these systems, including operator product expansions, bosonfermion correspondence, YangBaxter equation, different versions of Bethe Ansatz.

Michael Lashkevich 
63 per term

MA060276  
Optical Communications (Term 34)
Communication is an important part of our daily life. The communication process involves information generation, transmission, reception and interpretation. As needs for various types of communication such as voice, images, video and data communications increase demands for large transmission capacity also increase. This need for large capacity has driven the rapid development light wave technology; a worldwide industry has developed. An optical or light wave communication system is a system that uses light waves as the carrier for transmission. An optical communication system mainly involves three parts: transmitter, receiver and channel. In optical communication transmitters are light sources, receivers are light detectors and the channels are mainly waveguides (e.g. optical fibers) or free space.

Franko Kueppers, Arkady Shipulin 
63 per term

MA060157  
Optimization Methods
The course is devoted to optimization methods and optimization problems design with a special attention to those motivated by data science, engineering and industrial applications.
The course starts with a brief reminder of the foundations of convex analysis. Then we discuss zero, first and second order methods with a special focus on their efficient implementation. We distinguish between various problem classes, discuss suitable methods for every class. The problem formulation and its proper reformulation is the critical issue for an optimizer. We’ll learn about optimization models and convex relaxations. Special attention will be addressed to Linear Matrix Inequalities (LMI) that arise in optimization problem formulations. One of the home assignments is devoted to understanding the constraints of performance for different software packages. At the last part of the course we move further to advanced first order optimization methods such as proximal mirror descent and extra gradient methods and discuss how to utilize problem structure (e.g. sparsity and separability) to speed up the methods. Within engineering and practical sections, we show how to use the methods above to crack convex and nonconvex problems arises in engineering, energy systems, machine learning and related fields. 
Elena Gryazina  6  MA060002  
Organic Materials for Electronics, Photonics, Energy Generation and Storage
The course provides an overview of the latest achievements in the field of material design for electronics, energy conversion and storage.
The main purpose of the course is studying the basic chemical, physical and physicochemical, e.g. surface and structural, aspects of designing novel materials with the desired properties. This course will be focused mainly on organic and hybrid materials as well as on different types of electronic devices made thereof: fieldeffect transistors and electronic circuits, sensors, memory elements, light emitting diodes, solar cells, photodetectors, lithium and sodium batteries. Using a set of examples it will be shown how the discovery of novel materials results in the development of novel technologies, innovative products and, in some cases, even leads to revolutionary changes in specific fields of science and technology. This course is designed for MS students planning to perform experimental studies in the interdisciplinary fields at the boarder of physics and chemistry with the aim of solving relevant challenges of modern materials science. 
Pavel Troshin  6  MA060119  
Pedagogical Experience  Dmitry Artamonov  3  DE030005  
Pedagogy of Higher Education  Magnus Gustafsson  3  DE030025  
Perception in Robotics
This course will present the fundamental theory and application of perception techniques. The word perception on the context of this course will refer to the problems of Localization, Mapping and in general State Estimation. Today we are witnessing an explosion on the applications for this technology, originally developed on the robotics field, being outsourced to other domains such as selfdriving cars, augmented reality, flying drones, etc. Yet there are many challenges to be solved on a wide variety of research topics. The content of the course will be mainly based on a probabilistic approach to perception problems and will examine a selected set of contemporary algorithms in depth. Topics include Bayesian filtering; algorithms for mapping, localization and simultaneous localization and Mapping (SLAM); Observation and transition functions; Read below about the course policy, final project and other details.

Gonzalo Ferrer  6  MA060283  
Petroleum Geophysics
The course will provide a graduate level overview of geophysical methods
of hydrocarbon (HC) exploration; including classification, applications, integration; physical properties of rocks (density, susceptibility, resistivity, and seismic wave velocities). All types of geophysical methods will be thoroughly reviewed from a comprehensive geophysical applications but also from the standpoint of fundamental mathematical and physical principles. The course will study passive geophysical methods using the natural fields of the Earth, e.g. gravity and magnetic; but also, active geophysical methods that requires the input of artificially generated energy, e.g. seismic reflection. The objective of geophysics is to locate or detect the presence of subsurface structures or bodies and determine their size, shape, depth, and physical properties (density, velocity, porosity…) but also the fluid content (oil, gas , water) contained in the porous media. The course will introduce also modern techniques of geophysical interpretation based on modeling and inversion. 
Marwan Charara  3  MA030076  
Petrophysics and Well Log Interpretation
The course provides both theoretical knowledge in well logging application for reservoir characterization and practical skills in well logging processing and interpretation software.
During the course students will get familiar with the main well logging tools and methods, such as gamma, spontaneous potential, caliper, formation density, neutron, electrical, formation microimaging, sonic, magnetic resonance logging and so on. The students will study the well logs application for defining the key reservoir properties, correlation, integration with laboratory core test data. Besides lectures the course includes computer classes where students will gain applied skills in well logging interpretation software (Techlog). During the software practicums the participants will learn the main well logging data handling operations, such as creating a project for a field, import / export, displaying logs, data and variable management, depth referencing, constructing crossplots, calculating parameters, well correlation. The proportion of lectures and software classes is approximately 50% / 50%. 
Alexei Tchistiakov  3  MA030289  
Physics of Colloids and Interfaces
The interface science is the basis for modern nanotechnology. Objects of the microworld are dominated by surface effects rather than gravitation and inertia. The applications of interface science are important for labonchip technologies, microfluids, biochips, tissue engineering, biophotonics, theranostics. The peculiarity of modern interface science is a good example of interdisciplinarity. The interface science has become a really interdisciplinary field of research including physics, biology, chemical engineering, medicine. During this course the students gain not only theoretical knowledge, but also receive practical skills related to: 1) preparation of iron oxide nanoparticles and their characterization by dynamic light scattering method for determination of size and Zpotential of nanoparticles; 2) synthesis of calcium carbonate cores at micro and submicron size;3) loading of calcium carbonate particles by inorganic nanoparticles and proteins; 4) preparation of microcapsule shell using Layer by Layer assembly method formed on the surface of calcium carbonate microparticles and their characterization by fluorescent microscopy and Raman spectroscopy.They will receive a knowledge that can be used for analysis of phenomena in the microworld from point of view of interface science.

Dmitry Gorin  3  MA030310  
Plant Biotechnology lab (Term 34)  Eugene Lysenko 
63 per term

MA060331  
Plant Molecular Biology lab (Term 34)  Eugene Lysenko 
63 per term

MA060330  
Power Electronics
The course provides an overview of the latest achievements in power electronics. The main purpose of the course is to analyze different circuit topologies, to understand how they work and which are their benefits and limitations. The course starts with reviewing the basics in electric circuit theory, and then, it introduces different kind of semiconductor devices such as diodes, thyristors and transistors. After this, power electronics circuits are presented: rectifiers, DCDC converters and inverters. The course gives the tools to analyze any kind of power converters, and provides different examples related with microgrids and energy storage applications. It has three parts: lectures, home tasks and experimental activities in the lab. By the end of the course, the students should be able to analyze a power converter, to simulate it and to understand the possible applications.

Federico Martin Ibanez  6  MA060198  
Protein Chemistry and Engineering
Among biological molecules, proteins are undoubtedly the most diverse in structure and functions. This course describes basics of protein chemistry and intracellular functioning. The following main topics are discussed.
Protein structure: Protein functioning: Cofactors: Posttranslational modifications: Intracellular protein trafficking: Protein degradation: Protein engineering: 
Konstantin Lukyanov  3  MA030373  
Quantum Field Theory (Term 34)
At present time Quantum Field Theory (QFT) is the main theoretical tool used for the description of the phenomena occurring in the microworld. Examples include interactions between elementary particles, hadron structure and so on. At the same time, QFT methods are widely used in all areas of modern theoretical physics such as condensed matter physics, statistical mechanics, turbulence theory and others. Moreover, the creation of QFT has stimulated the development of many modern areas of mathematics.
The course is aimed at the study of the basic ideas and methods of QFT, as well as the discussion of its applications in various areas of modern theoretical and mathematical physics. Topics include quantization of scalar and gauge theories, path integral approach, perturbative expansions and Feynman diagrams, (1+1) dimensional exactly soluble models and some other ideas of modern science. 
Andrei Semenov 
63 per term

MA060316  
Quantum Integrable Systems (Term 34)
The course is devoted to quantum integrable systems. The history of quantum integrable systems starts from 1931 when
H.Bethe managed to construct exact eigenfunctions of the Hamiltonian of the Heisenberg spin chain with the help of a special substitution which became famous since that time (ansatz Bethe). In one or another form this method turns out to be applicable to many spin and fieldtheoretical integrable models. From the mathematical point of view, Bethe's method is connected to representation theory of quantum algebras (qdeformations of universal enveloping algebras and Yangians). Here is the list of topics which will be discussed in the course. – Coordinate Bethe ansatz on the example of the Heisenberg model and – Bethe ansatz in exactly solvable models of statistical mechanics – Calculation of physical quantities in integrable models in thermodynamic – Bethe equations and the YangYang function, caclulation of norms of Bethe – Quantum inverse scattering method and algebraic Bethe ansatz, quantum Rmatrices, – Functional Bethe ansatz and the method of Baxter's Qoperators, functional The knowledge of quantum mechanics and statistical physics for understanding of 
Anton Zabrodin 
63 per term

MA060315  
Quantum Mesoscopics. Quantum Hall effect (Term 34)
The course of lectures consists of two roughly equal parts. The first part begins with an account of the physics of twodimensional electrons in a perpendicular magnetic field and attempts to explain the phenomenon of an integer quantum effect for shortrange and smooth random potentials. The presentation in this part is supposed to be quite accessible to students familiar with quantum mechanics and diagram technique. In the second part of the course, the fundamentals of the fieldtheoretical description of the phenomenon of an integer quantum Hall effect in a shortrange random potential are presented. To understand the material of the second part, students need to know the methods of functional integration and quantum field theory.

Igor Burmistrov 
63 per term

MA060278  
Quantum Theory of Radiation and Quantum Optics (Term 1B4)
The main goal of the course is to study by students basic physical principles, main quantum electrodynamical (QED) phenomena and mathematical apparatus of quantum electrodynamics and quantum optics. Students must know theory and experimental data on interaction of radiatiation with matter. Particularly will be discussed: quantum theory of electromagnetic field, problem of phase in QED, coherent and squeezed states, relativistic quantum theory of electrons and positrons, Klein paradox, diagram technique,
divergences and renormalization of mass and charge of electron, Lamb shift, cavity quantum electrodynamics (including last achievements), dynamical Casimir effect, basics of united theory of electromagnetic and weak interactions etc. 
Yuri Lozovik 
61.5 per term

Options  MA060314 
Quiver Representations and Quiver Varieties (Term 34)
The theory of quivers is one of the central topics in various fields of modern mathematics and mathematical physics, such as algebraic geometry, representation theory, combinatorics, quantum field theory, integrable systems. The theory has lots of beautiful and deep theorems and is very popular due to a huge number of applications, including McKay correspondence, instantons and ADHM construction, geometric realization of the KacMoody Lie algebras. Many of the recent results and applications of the theory of quivers are based on the quiver verieties, introduced by Hiraku Nakajima 20 years ago. The course will cover the basic material on the structure theory of quivers and their representations, such as path algebras, Gabriel's theorem, Hall algebras, preprojective algebras and AuslanderReiten quivers. Based on the general theory of quiver representations we will discuss the definition of the Nakajima quiver varieties and several explicit examples and applications. The course is aimed at the graduate students or advanced bachelor students. The basic knowledge of algebraic geometry, differential geometry, and the theory of Lie groups and Lie algebras is expected.

Evgeny Feygin 
63 per term

MA060425  
Research (Term 58)  Mikhail Skvortsov 
61.5 per term

MA060432  
Research Methodology: Computational and Data Science and Engineering (Term 23)  Maxim Fedorov 
31.5 per term

DA030102cds  
Research Methodology: Molecular Biology  Konstantin Severinov  3  DA030403  
Research Methodology: Molecular Biology Seminar
Main topic of term2 seminar will be "CRISPR – the beginnings"
For each class, there will be a paper that two people will present to the rest of the class. We will go down to the details of experiments – how things were done and what do the data/figures really show, so be prepared to answer indepth questions. Presenters will start by stating the name of the paper/main authors and telling the take home message of the paper – why it is signficant, what problem it solved. Then they will proceed to the actual work. If there are methods/results mentioned in the paper that refer to prior work, you shall be prepared to answer questions about it too. The audience is supposed to read the paper being discussed beforehand and participate in discussions. To pass, one would need to present a paper at least once during the module and actively take part in discussions of other papers. One absence is allowed no questions asked. Additional absences when unexplained will be a cause for nopass grade. There will be a few home assignments. They must be submitted in time, typed–not written up–and done professionally (written in good language, be concise and free of spelling errors – consider them as part of academic writing exercises). It is gonna be fun – students tend to like the seminar and its atmosphere Dear students, Please note that the final list of participants will be selected by prof. Severinov after registration closes. 
Konstantin Severinov  3  DA030102ls  
Research Methodology: Space Center Seminar (Term 14)
The seminar will cover current topics in the space domain: latest news, discoveries. Also planned that all PhD students and some Master students will present their research. External lecturers will be invited regularly to focus on the main applications of space technologies: science, telecommunication, navigation and remote sensing. Aspects of space technologies will also be discussed: structures, software, attitude determination and control systems, on board computers, communication system power supply systems and others. The seminar will be offered in English.

Anton Ivanov 
30.75 per term

DA030102es  
Research Seminar "Advanced Materials Science" (Term 28)  Keith Stevenson 
30.5 per term

DA030302  
Research seminar "Energy Systems and Technologies" (Term 24)
This research seminar is the general meeting for faculty, researchers and master and PhD students of Energy Systems programs. The seminar takes place every week during Terms 2(6)3(7)4(8).
Master students must attend the seminar at least for one academic year but welcome to attend during two years. PhD students are welcome to attend the seminar during all years of studies but can gain no more than 6 credits in total. The seminar consists of faculty lectures, invited lectures of top scientists in their research field as well as students’ reports on their own or examined papers. To PASS the course and gain 3 credits per academic year the student must fulfill all three requirements: 1. Attendance: > 2/3 of seminars. 2. Presentation. Depending on the status: 3. Evaluation. Filling in the Online feedback form. The core of the selfstudy activity will be preparation to the talk that is comparable to project implementation (a significant part of many regular courses). The students are expected to assign at the beginning of Term 2/6 and may drop the seminar till the beginning of Term 3/7 while credits are provided in Term 4/8. 
Elena Gryazina 
31 per term

MA030386  
Research seminar "Modern Problems of Mathematical Physics" (Term 14)
Course "Modern problems of mathematical physics" is a student seminar, so participants are expected to give talks based on the modern research papers. Current topic of the seminar can vary from time to time: now it is devoted to the study of N=2 supersymmetric gauge theory and its links with random matrix models, ABJM theory, localization, complex curves, and integrable systems. Other topics that were already covered, or can be covered in the future, are: classical integrable equations, complex curves and their thetafunctions, quantum integrable models (quantummechanical and fieldtheoretical), models of statistical physics.

Pavlo Gavrylenko 
61.5 per term

DA060268  
Research seminar "Modern Problems of Theoretical Physics" (Term 14)
Research seminar "Modern Problems of Theoretical Physics" is supposed to teach students to read, understand and represent to the audience recent advances in theoretical physics. Each student is supposed 1) to choose one of recent research papers from the list composed by the instructor in the beginning of each term, 2) read it carefully, 3) present the major results of the paper to his/her colleagues during the seminar talk, 4) answer the questions from the audience about the content of the paper. The papers in the list are selected, normally, from the condensed matter theory and related fields, like: physics quantum computing, statistical physics, etc. The papers to the list are usually chosen from most competitive physics journals, like Nature Physics, Science, Physical Review Letters, Physical Review X and others.

Mikhail Feigelman, Konstantin Tikhonov 
61.5 per term

DA060319  
Review of Materials and Devices for Nano and Optoelectronics (Term 34)
The lectures are presented by the scientists working actively in various directions of nanoelectronics and optoelectronics in Russia and abroad. Seminars assume the discussion of recent original papers in the area (including superconducting electronics and spintronics, terahertz waves technology and applications, quantum coherent systems (qubits), single electron devices). The classical papers presenting a physical basis for devices operation will be also considered. The papers are distributed in February. Each student is expected to report two papers during the period FebruaryMay.

Valery Ryazanov 
63 per term

MA060206  
Satellite Navigation
The GNSS data processing course is aimed to cover the modern state of technology in global navigation satellite systems applications for precise surveying, agriculture robotics, road construction and other applications. Course participants will become familiar with subjects such as:
– Navigation observables and navigation solution, – Single, double, triple difference techniques, – Precise point positioning, – Realtime relative positioning, – Carrier phase ambiguity resolution and integer lattice reduction, – Anomalies detection and isolation, – Basics of satellite receivers firmware design, – Geodetic surveying and practical using of GNSS receivers for accurate surveying, – Using GNSS navigation for attitude determination and motion control for wheeled robots, UAV's and other applications. 
Lev Rapoport  6  DA060380  
Selected Topics in Energy: Physical, Chemical and Geophysical Challenges (Term 24)
The course provides an introduction to the modern topics related to fundamentals of exploration of energy resources, energy generation, storage, conversion and use. It identifies the corresponding practical challenges to be addressed at the fundamental research level and familiarizes the students with the stateoftheart approaches, methods and techniques in use in related scientific areas. The course seeks to emphasize and maintain interdisciplinary nature of the energyrelated topics, in particular, combination of micro and macroscopic approaches of geophysics, mechanics and chemistry in hydrocarbon exploration and development, relation between the physical and chemical processes of energy generation and conversion, integration of physical, chemical and mechanical approaches to perspective materials (physical and chemical synthesis, micro and macroscopic characterization, structureproperty relations, etc.) and related theoretical methodologies. These interdisciplinary links are mostly demonstrated by horizontal knowledge exchange among the students reporting and discussing practical examples from their own research field or from modern review or research publications. Topical lectures are included for further exploration of these links. The secondary aim of the course is the development of presentation skills (oral and writing), as well as scientific peerreview experience. The seminar format chosen for most activities allows students free exchange of knowledge and ideas, broader vision of their research projects and methodologies, better assessments of their own research skills and demands for further education.

Alexei Buchachenko 
62 per term

DA060106  
Spacecraft and Mission Design
The main objective of the course is to introduce the concept of space system design and engineering. The course will describe the various subsystems involved in the design of a satellite. It will also describe the techniques of systems engineering that are used to obtain a coherent satellite design.
This class will focus on concept preparation in the Vdiagram logic. Further results can be explored either in the Space Sector course, where commercial aspects of the mission can be considered, as well as in the PLM course, where technical details can be worked out in a systematic fashion. 
Anton Ivanov  6  MA060074  
Spectroscopy of Quantum Materials
The term “quantum materials” unites a broad class of very different materials demonstrating genuinely quantum behavior. Quantum materials include superconductors, strongly correlated systems, systems of massless Dirac electrons, topological materials, novel twodimensional crystals etc. Research of quantum materials is in the vanguard of modern photonics and condensed matter physics.
The goal of this course is to give a broad review of basic models and modern spectroscopic studies of quantum materials. The course requires basic knowledge of quantum mechanics, optics and solid state physics. In the introductory part of the course, the basic classical and quantum models of electromagnetic response are considered, and the most widely used modern methods of spectroscopy are outlined. The rest of the course describes such quantum materials as graphene and graphenebased structures, topological insulators, topological Dirac and Weyl semimetals, strongly correlated materials, twodimensional transition metal dichalcogenides, oxide interfaces, and novel engineered quantum materials. The students will be introduced to basic models and to both conventional and ultrafast pumpprobe spectroscopy studies of these materials. 
Alexey Sokolik  3  MA030162  
Statistical Learning Theory
This is an introductory MS/Ph.D. level course in the theory of machine learning. Our primary focus is a theoretical analysis of prediction methods, including statistical and computational aspects. There are no formal prerequisites for this class. But we will assume a significant level of mathematical maturity. This means an understanding of linear algebra, analysis, and probability. Convex optimization and machine learning will be extremely helpful but is not strictly necessary. Despite the theoretical nature of the course, students will be given a lot of practical exercises. Thus we expect knowledge of at least one programming language (Python, Julia, R, or C/C++)

Yury Maximov  3  MA030417  
Structure and Properties of Materials
This course is an introductory subject in the field of materials science and crystallography. The goal is to introduce students to basic concepts of structureproperty relations for materials at the microscopic level.
Independent student work on discipline includes preparation for lectures, seminars, labs and other learning activities, as well as the implementation of individual tasks / independent works / projects and others. Educational and methodical support of Independent student work presented by topics of all kinds of tasks and guidelines for their implementation. 
Artem Oganov  6  MA060075  
Technology Planning and Roadmapping: Foundation
Technology Planning and Roadmapping (TPR) is a key corporate function that companies put in place to understand, manage, and define technology strategy. The main goals of TPR are:
1) to provide understanding on current technology investments in the company (portfolio management); 2) to identify technology investment options for future products and services (landscaping); 3) to benchmark the company’s technology strategy against market competition and accounting for global technology trends (benchmarking); 4) to valuate future financial benefits, risks, and technical feasibility of envisioned technology investments (valuating); 5) to prioritize technology investments by analyzing potential future scenarios while accounting for corporate strategic drivers (prioritizing); and ultimately 6) to formulate recommendations for research and development (R&D) investments based on the definition of a rigorous technology strategy (planning). Technology Planning and Roadmapping: Foundations (TPR:F) covers the theoretical fundamentals of technology planning and roadmapping, including fundamental concepts, an overview of the most common tools and processes used by practitioners in the field, and application examples from companies in different sectors. In short, TPR:F is about building the intellectual foundations that will allow students to collaboratively build a TPR system for an industrial organization. The main deliverable of TPR:F is the development of a technology roadmap for a student startup or reverseengineering of the roadmap of a company of interest to the student. 
Alessandro Golkar  3  E&I  MC030017 
Thermal Fluid Sciences
The course is designed to give an overview of the fluid mechanics, gas dynamics, thermodynamics, and electromagnetic phenomena in fluids and gasses. The following topics are discussed:
1. Kinematics of continuous media 2. Basic concepts and equations of fluid dynamics and thermodynamics 3. Models of fluid and gas media 4. Contact discontinuities in fluids, gases, and plasma 5. Flow of ideal, incompressible fluid 6. Incompressible viscous flow. Boundary layer theory. Turbulence 7. Compressible fluid flow. Gasdynamic 8. Electromagnetic phenomena in fluids Students will have to complete daily homework, theoretical, computer, and design projects, midterm and final exams. 
Iskander Akhatov  6  MA060053  
Thermal Spray Coatings (Term 34)
Thermal spray technology provides a costeffective functional surface solution for many applications requiring resistance to wear, heat, and corrosion. This practicallyoriented course is intended to familiarize graduate students with an understanding of thermal spray processing science and frontline research topics, with attention to latest development and innovations in the field. The second purpose of this interdisciplinary course is to give the students technological/engineering perspectives of thermal spray applications and practice.
Students’ key learning objectives: 
Igor Shishkovsky 
63 per term

MA030356 
Course Title  Lead Instructors  ECTS Credits  Stream  Course Code 

Academic Communication: Preparatory English for Phd Exam (Term 34)
Efficient professional communication is the key to Academic success. The course is designed for PhD students who want to maximize their academic potential by boosting their ability to write research papers, present in front of multidisciplinary audiences, participate in scholarly discussions and engage in other forms of academic communication.
The main goal of the course is to enable PhD students to produce clear, correct, concise and coherent texts acceptable for the international professional community. The course is designed for a multidisciplinary audience. The course serves as a preparation for the qualification language exam, which is a prerequisite for the Thesis defense. 
Elizaveta Tikhomirova 
31.5 per term

DE030029  
Academic Writing Essentials (Term 34)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030002ls 
Academic Writing Essentials (Term 34)
Academic writing skills are necessary for effective research, innovation, and educational activities in a multinational setting. The aim of the course is to provide guidelines and strategies for writing academic texts, focusing on relevant aspects of grammar, vocabulary, and style. The course includes analysis and practice of various forms of scientific and technical writing, and builds writing skills from sentences to paragraph structure, from summary to abstract, and lays the foundations for writing scientific papers and Master Thesis.
Modern science is, for most purposes, a collective collaborative effort, so the course is designed to promote individual and group responsibility by providing mutually related and timedependent tasks, such as peer review. The course is writingintensive with ample opportunity to practice editing and peerreviewing. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030002 
Advanced Materials Modeling
The course builds on introductory Computational Chemistry and Materials Modeling course to provide indepth understanding and advancedlevel use of commonly employed modeling methods, as well as teach state of the art methods tailored for modeling of specific classes of materials and physical processes relevant to multiple major industries in the future, including nanotechnology and energy. The emphasis is on deep understanding and practical use of techniques, algorithms and programs to bridge theory and applications, from the discovery of materials to their use in realworld technologies. Personalized advisory of several experts in different areas of computational materials science will allow students to accomplish challenging projects related to their MSc/PhD theses or other research in materials science.
At the end of the course, students will learn advantages and limitations of various approximations in electronicstructure modelling, both within the framework of densityfunctional theory and beyond (including manybody perturbation theory). Methods for describing effects of external factors such as temperature, pressure, and doping on properties of materials will be also discussed. Students will also learn modern methods of artificial intelligence for materials design. During practical lessons students will learn to perform calculations of atomic and electronic structure of materials and evaluate reliability of obtained results. Students will also have an opportunity to apply in practice molecular dynamics based methods, as well as machine learning methods. Students will master electronicstructure packages Abinit and FHIaims, as well as other programs, including advanced molecular dynamics and machine learning algorithms. 
Sergey Levchenko  6  MA060341  
Advanced PLM techniques: Product Prototyping
The main goal of the course is the familiarization with digital manufacturing and prototyping.
During the course, students should develop the technology for Formula Student car prototype production. The course provides students with a theoretical and practical basis for advanced manufacturing of complex systems, such as cars and forms the understanding of the product lifecycle management. 
Ighor Uzhinsky  6  MA060253  
Biomaterials and Nanomedicine
This module will define and describe biomaterials in general term with particular attention to modern concepts of nanomedicine. It will include basics in properties of Biomaterials Surfaces considering their Physics and Chemistry, Methods of surface modification and characterization, approaches to fabricate Biocompatible surface. This will follow aspects of Protein – surface and CellSurface interaction. Biomaterials part concludes with fabrication and use of Scaffolds, implants, eluting stents and gels for tissue engineering
Nanomedicine part includes overview of Micro & Nanoparticles application as biomaterials, concept of Drug Delivery systems, Controlled and Triggered release Course include considering recent original and review paper by students and lab work on formation of biomaterials of certain sort and their characterisation 
Gleb Sukhorukov  3  MA030405  
Biomedical Application of Photonics
The overview of current state of photonics application in the biology and medicine will be presented including optical properties of cell, biological tissue, body (absorption, reflection, scattering, fluorescence). Now the photonic tools are used for imaging, diagnostics, manipulation, therapy and surgery at three different levels – cellullar, tissue and body, therefore the course aims to teach students to understand basic principles of the current biomedical applications of photonics tools. The every level is required to apply different approach, for example for cellular level imaging, manipulation, Confocal LS Microscopy (including technology of quotative analysis as FRAP, photoconversion, FLIP, FLAP, FRET, FLIM, FCS, FCCS), dark field microscopy; optical tweezers approach, laser cell poration; for diagnostics – Raman microscopy, CARS, in vitro and in vivo fluorescent flow cytometry, in vivo flow photoacoustic (PA) cytometry; and for therapy – laser induced necrosis and apoptosis; in vivo flow PA setup for theranostics are used. Tissue level requires for imaging, multiphoton microscopy, SHG and THG microscopy, OCT, rasterscan optoacoustic mesoscopy (RSOM); for manipulation – laser 3D printing, laser skin perforation. Body level includes for imaging – OCT, MRI, CT, MRI, fluorescence and optoacoustic imaging, US, PET; for diagnostics – different types of in vivo sensors including implantable medical devices, smart tattoo; for therapy – photodynamic and photothermal therapy; for surgery – photonic approach guided surgery including endoscopy, high speed surgery with the highest resolution. Topics also include description of different types of contrast and optical clearing agents. The course will also offer a practice in operation of imaging systems on the cell, tissue and body level such as fluorescent microscopy, RSOM, fluorescence imaging. Students will have experience related to application the most appropriate photonic tools for their own research projects.

Dmitry Gorin  6  MA060158  
Biomedical Imaging and Analytics
This course is designed for Machine Learning and DataScience students who would like to concentrate their research on the analysis of biomedical images. This cohort of specialists – especially early on in their careers – is known for dismissing both the physical mechanisms of image formation and the very biological rationale behind a given imaging modality. In this course, we will attempt to reunite the three disciplines in order to help students develop systematic analytical expertise and biological intuition.
The course is also aligned with the curriculum of the centers of life sciences and photonics and should be used for enriching those offerings with modern machine learning and image analytics skills. Students will learn what forms the backbone of biomedical imaging, drawing from the mathematical, physical, chemical, and biological sciences, including the subjects of: • Light microscopy (live cell imaging, deconvolution and superresolution microscopy, 3D microscopy, Optical Coherence Tomography); • Medical imaging (Xray, Computed Tomography, Magnetic Resonance Imaging, Ultrasound, Positron Emission Tomography); • Image analytics (filtering and signal processing, machine learning and artificial neural networks, computer vision, imagebased biological and physiological modeling). The course is offered primarily for CDISE students who are assumed to know the basics of image processing and machine learning. In addition to the lectures, there will be 6 adapted seminars for those students who encounter the technical aspects of this course for the first time (e.g., Life Sciences students). The technical sessions will be shuffled with invited seminars by doctors/biologists with whom there is an ongoing collaboration. 
Dmitry Dylov  6  MA060305  
Cell Biology Lab Course
Lab course in Cell biology provides students an opportunity to explore how the techniques of molecular and cell biology may be used to understand cell function. Laboratory practice in cell biology will provide the experience in genetic manipulations with cell lines, immunostaining and fluorescence or confocal microscopy analysis. The main aspects for FACSanalysis and cell sorting will be introduced. The approaches for gene expression analysis by RTqPCR, Western blot and differential proteome analysis will be used to understand the influence of genetic manipulation to the cell function. The introduction in powerful approach to understand the protein interaction such as SPR optical biosensor will be provided.
The introduction in highthroughput screening of biologically active compounds will be provided. The course will provide students with a handson understanding of modern methods of cellular manipulation and understanding the mechanism of cell functioning. 
Olga Dontsova  6  MA060134  
Communication Technologies for IoT
This is a newly developed course that prepares students for the applying modern telecommunication technologies, both wired and wireless in the Internet of Things area.
The course combines lectures and labs related to hardware, transmission techniques, the mediumaccess control layer, networking, applications and standards for the IoT communication technologies. All technologies are considered with usecase based approach that shows their practical application in real industrial and research scenarios. 
Dmitry Lakontsev, Kirill Andreev 
3  MA030234  
Computational Materials Science Seminar (Term 28)  Dmitry Aksenov 
30.5 per term

MA030430  
Condensed Matter Spectroscopy and Physics of Nanostructures (Term 1B4)
This course presents a modern introduction to the field of optical phenomena in condensed matter and nanostructures. The first part of the course starts from the classical and quantum theory of electromagnetic response, and basics of the condensed matter spectroscopy. Then the major research directions in the modern condensed matter spectroscopy are considered, such as spectroscopy of graphene, topological materials, and twodimensional transition metal dichalcogenides. The second part of the course is focused on specific optical phenomena in semiconductors, heterostructures, nanostructures and interfaces, such as surface plasmons and polaritons, excitons, spinorbit coupling effects, Raman scattering and color centers.

Anatoly Mal’shukov 
61.5 per term

Options  MA060313 
Data Analysis for Space Weather  Tatiana Podladchikova  6  DA060309  
Deep Learning
The course is about Deep Learning, i.e. a new generation of neural networkbased methods that have dramatically improved the performance of AI systems in such domains as computer vision, speech recognition, natural language analysis, reinforcement learning, bioinformatics. The course covers the basics of supervised and unsupervised deep learning. It also covers the details of the two most successful classes of models, namely convolutional networks and recurrent networks. In terms of application, the class emphasizes computer vision and natural language analysis tasks. The course involves a significant practical component with a large number of practical assignments.

Victor Lempitsky  6  DA060057  
Developing Products and Services through Design Thinking  Alexander Chekanov  3  E&I  MC030029 
Electrochemistry: Fundamentals to Applications
This course covers fundamental concepts of electrochemistry: oxidation and reduction processes, types of conductors, electrolytes, classification of electrodes and electrode reactions, Faraday’s Laws, and electroanalytical methods. In addition, some applied aspects of electrochemistry will be covered including industrial electrolytic processes, electrodeposition, and electrochemical power sources (batteries and fuel cells).
The prerequisites are: undergraduate math, chemistry, and physics. 
Keith Stevenson, Victoria Nikitina 
6  MA060127  
Energy Colloquium
The Energy Colloquium educates the audience in the presentday research and applications within the broader field of Energy Science and Technology. The Colloquium consists of a series of presentations by invited academic and industry speakers. The presentations target a nonspecialist audience.
All Master and Ph.D. students within the Energy Program are encouraged to attend the Energy Colloquium during the entire period of their studies. Students can earn 1 credit, if he/she participates in the Energy Colloquium over the course of any 2 terms of the academic year. Students who passed one round can make next (for credit) over the course of their subsequent studies. 
Alexei Buchachenko  1  Extra  MF010092 
Engineering Physics
Engineering Physics course have been designed to help students gain an understanding of the key elements intrinsic to the subject. Engineering Physics deals with the physics of substances that are of practical utility. This course focuses on the changes in properties of materials arising from the distribution of electrons in metals, semiconductors and insulators. It covers topics on crystallography, free electron theory of metals, principles of quantum mechanics, superconductivity, properties of dielectrics and magnetic materials, lasers, fiber optics, holography, acoustics of buildings and acoustic quieting, optics, nondestructive testing using ultrasonics, nuclear physics, and electromagnetic waves. A list of important formulae, solved problems, and review questions will be considered for the recitations.

Iskander Akhatov, Vladimir Drachev 
3  MA030434  
English. Candidate Examinations
This is a blended metacourse for the English Qualification Exam needed for the Russian PhD Degree. The Exam is designed as a multidisciplinary conference where the participants present results of their PhD research and follows the general principles of conference materials submission, peer review, resubmission, presentation, and discussion.
The goal of the Exam is Academic Communication, so the participants should demonstrate the ability to present their research results in front of a multidisciplinary audience and deliver the key ideas in good Academic English in terms of vocabulary, grammar and style. Preexam/ preconference activities, such as material submissions and peer reviews, last of three weeks and take place fully online. They include: Project proposal V1+ 2 Peer Reviews; a 2minute video annotation V1 + peer review; and a stack of presentation slides V1+ peer review. Version 2 of the Proposal, video annotation and the slides should be improved using the comments of the Instructor and the peers. Depending on the applicable regulations related to COVID19, on the Examination day students make their presentations and participate in the discussion in person or via an online platform in front of the Examination Committee and a group of peers. Failure to submit an assignment by the due date may result in the loss of the grade. The participants will practice a variety of academic skills: – Planning and designing a wellstructured and balanced presentation The grade is counted towards the PhD Qualification. 
Elizaveta Tikhomirova  3  DE030003  
Experimental Optics  Sakellaris Mailis  6  MA060336  
Functional Methods in the Theory of Disordered Systems (Term 34)
The course provides an extensive overview of contemporary functional methods in the theory of disordered systems. Starting from the theory of random matrices, it covers various aspects of electron motion in disordered media. The concept of the nonlinear supersymmetric sigma model is introduced and used as a unique language to describe such phenomena as energy level statistics, weak localization, renormalization group analysis, nonperturbative solution of the localization problem in quantum wires. Finally, functional integral method is used to address electronelectron interaction in disordered metals and nonequilibrium phenomena in quantum dots.

Mikhail Skvortsov 
63 per term

MA060262  
Fundamentals in Methodology of Scientific Research (Term 34)
The course can be considered as a tutorial for MS and PhD students performing R&D projects within their educational tracks (e.g. while preparing thesis) and extracurricular activities focused on building scientific or entrepreneur career. In the frame of the course, we will explore the most efficient strategies for performing R&D projects starting from planning the research program and ending up with the dissemination and application of the obtained results, e.g. by filing patents, licensing or making startups. Using a set of examples, we will discuss how to address the most common challenges in scientific research and present the obtained results in a proper way. In particular, students will be actively involved in practical trainings learning how to analyze a potential impact of their results, prepare conference presentations, scientific publications and research projects. This course is designed mainly for MS and PhD students involved in experimental studies in interdisciplinary fields, mainly at the interface of physics and chemistry, aiming to address relevant challenges of modern materials science.

Pavel Troshin 
63 per term

MA060342  
Fundamentals of Optics of Nanoscale Systems (Term 1B4)
The course focuses on the general concepts and experimental developments in the rapidly evolving field of the modern physics of nanosized systems. It covers a broad spectrum of optics on the nanometer scale, ranging from fundamental nanoscience to nanotechnology applications. Topics covered include: foundations of lightmatter interaction at nanoscale, concepts of nearfield and quantum confinement, nanoplasmonics, optical emission of pointed nanoparticles (fluorescent molecules, quantum dots, plasmonic nanoparticles et al). Various experimental methods that used in nanooptics and nanoscience, including nearfield and farfield optical microscopy of subdiffraction spatial resolution, are presented. Nanophotonic devices, photonic crystals, spasers, singlephoton sources, nanosensors are discussed. Seminars assume the discussion of papers presenting a physical basis for nanoscale optical phenomena, as well as the papers describing the last achievements in the area.

Yuri Vainer 
61.5 per term

Options  MA060437 
Fundamentals of PostQuantum Cryptography  Grigory Kabatyansky  3  MA030408  
Gauge Fields and Complex Geometry (Term 34)
1. Selfduality equations, Bogomolny equations.
2. Relation to holomorphic bundles. 3. Relation to holomorphic bundles on twistor space. 4. Conformal symmetry and complex geometry in twistor space. 5. Elements of superfield formulation of SUSY field theories. 6. Chirality type constraints and complex geometry. 7. Some examples of superfield theories which require complex geometry. 8. BPS conditions in SUSY theories and complex geometry. 9. Elements of Hitchin's integrable systems and related complex geometry. 
Alexey Rosly 
63 per term

MA060178  
Geometric Modeling
Classification, principles and techniques of digital modelling of point sets are presented for points, curves, surfaces and solids. Specifically these include methods of modelling of point clouds, depth fields, parametric curves and surfaces, implicit surfaces and solids. Solid modelling includes such representations as Constructive Solid Geometry (CSG), Boundary Representation (BRep) with polygonal meshes and parametric surfaces, sweeping, spatial occupancy enumeration, and Function Representation (FRep).

Alexander Pasko  6  MA060297  
Geometrical Methods of Machine Learning
The course is elective for MSc program in Data Science at Skoltech.
Many machine learning problems are fundamentally geometric in nature. The general goal of machine learning is to extract previously unknown information from data, which is reflected in the structure (underlying geometry) of the data. Thus, understanding the shape of the data plays an important role in modern learning theory and data analytics. Realworld data obtained from natural sources are usually non uniform and concentrate along lower dimensional structures, and geometrical methods allow discovering the shape of these structures from given data. Originally being part of dimensionality reduction research, geometrical methods in machine learning has now become the central methodology for uncovering the semantics of information from the data. The aim of the course is to explain basic ideas and results in using the modern geometrical methods for solving main machine learning problems such as classification, regression, dimensionality reduction, representation learning, clustering, etc. A large part of the course addresses to most popular geometrical model of highdimensional data called manifold model and introduces modern manifold learning methods. Necessary short information on differential geometry and topology will be given in the course. The course lets students to be involved in meaningful reallife machine learning projects, such as mobile robot navigation, neuroimaging, to cope with challenging problems. 
Alexander Bernstein  3  MA030169  
Geostatistics and Reservoir Simulation
The course includes lectures in reservoir simulation, history matching, and fundamentals of geostatistics.
Reservoir simulation and history matching embrace the following: 1) Fundamentals of singlephase and multiphase multicomponent fluid flow and storage in reservoirs 2) Numerical solution of governing equations using finite difference 3) Introduction to inverse theory and history matching 4) Simulating of laboratory PVT data by Equation Of States (EOS) Fundamentals of geostatistics include the following: 1) Stochastic reservoir simulation 2) Statistical measures 3) Univariate and multivariate Statistics 4) Covariance and variograms 5) Sequential Gaussian simulation 6) Uncertainty quantification Finally, reservoir simulation and geostatistical analysis are integrated for risk analysis and economy estimation. Laboratory computational exercises are also included. 
Dmitri Koroteev  6  MA060085  
High Performance Computing and Modern Architectures
High Performance Computing refers to accumulation and usage of computing power well beyond a typical desktop or laptop computer. This is a main course for various aspects of HPC and a further development of the Scientific Computing course. Together with the theoretical part and discussion of basic parallel algorithms, the course will have a practical component aimed at solving different research and industryrelated problems on different computing architectures, such as modern CPUs and GPUs. The course will provide sufficient knowledge and experience in using standard parallel libraries (such as OpenMP, MPI and CUDA) as well as visualization software (ParaView, Visit). Students will be given a chance of using Skoltech's worldclass HPC facilities to learn typical methods and rules of working on the largescale collectively used supercomputers. The course is designed in such a way that students who successfully pass the exam will be able to use advanced methods of HPC in their everyday work.

Sergey Rykovanov  6  MA060287  
Imaging in Biology
Overview of current imaging research techniques in basic biomedical research. Various applications in neurobiology, cancer biology and preclinical studies of novel and emerging advanced microscopy technologies. Analysis of experiments and research described in recent scientific papers. The introduction of the course also includes core mathematics and optics. The course will outline and compare different optical microscopy techniques and superresolution imaging in biomedical research. Topics also include clearing agents and techniques, optical imaging of brain activity in vivo using genetically encoded probes, immediate early gene mapping, intravital imaging, applications for functional analyses of neuronal circuits. The course aims to teach students to understand basic principles of the current imaging techniques, microscope design, and image formation. The course will also offer laboratory practice in sample preparation, confocal imaging, and image analysis. Students will learn how to choose the most appropriate imaging method for their own research project.

Dmitry Artamonov  6  MA060118  
Immunology
The purpose of the course “Immunology” is to lay the foundation for understanding the principles of organization, basic algorithms and rationale of the immune system. Such basis is necessary for the further professional growth either in the field of fundamental immunology or applied research and development in medical immunology. This course will also be important for those who wish to professionalize in medical practice, pharmaceutical industry, epidemiology and health services management, engineering and business in the field of modern biomedicine.
The course is focussed on the human immune system, towards clinical applications. The first part should help to form a systematic view of the architecture of the immune system. Next, the main medical aspects related to the functioning of the immune system will be considered, including autoimmune diseases, hypersensitivity reactions, cancer immunology, immunotherapy, vaccinations, autologous and allogeneic blood cells transplantation. Special attention paid to adaptive immunity and stateofart bioinformatic approaches to the analysis of the Tcell receptor and antibody repertoire, the search for diagnostically and therapeutically relevant markers of adaptive immunity. In addition to the main program, PhD students and the boldest MS students will be offered to run a short, teamup, publicationoriented biomedical project. 
Dmitriy Chudakov  6  MA060172  
Innovation and Intellectual Property Studies Doctoral Seminar (Term 25)  Kelvin Willoughby 
61.5 per term

E&I  DC060009 
Intellectual Property, Technological Innovation and Entrepreneurship
The successful development of innovative technology ventures depends substantially on how well their intellectual property (IP) assets are protected, managed and leveraged. For technology entrepreneurs, skill in the management of IP is at least as important as skill in managing technology, people, organizations and business.
It is almost impossible for engineers or scientists to avoid confronting issues related to intellectual property. These issues include: the risk of violating the IP rights of others; an obligation to respect the IP policies of one’s employer; the need to obtain IP protection for one’s own inventions and creative works; the obligation to become involved in the management of the IP belonging to one’s employer; generating strategies for extracting value from one’s intellectual assets; and the challenge of ensuring that one’s own IP rights are not infringed by others, including by one’s own employer or one’s clients. In addition, given that such a large amount of contemporary business—in both the private sector and government—involves outsourcing and interorganizational collaboration, expertise in the licensing of intellectual property rights is in high demand. The management of intellectual property may often also involve artfully connecting proprietary strategies with open innovation strategies. This course will survey basic concepts of intellectual property and provide an introduction to a variety of types of intellectual property and IPrelated rights, such as patents, copyright, trade secrets, trademarks, design rights, database rights, domain names, and demarcations of origin. The course will also examine the strategic management of IP in the process of technology commercialization, and the resolution of IPrelated conflicts between technologybased enterprises. It will place special attention on the IP challenges faced by entrepreneurial technology ventures. 
Kelvin Willoughby  6  E&I  MC060006 
Introduction to Quantum Theory (Term 34)
One of the most striking breakthrough of the XX century is the creation of the entirely new area of physics named quantum physics. It emerged that the whole world around us obeys the laws of quantum mechanics, while the laws of classical physics that we are familiar with (such as, for example, Newton's equations) describe only macroscopic objects and can be obtained in limiting case. After that a lot of phenomena in different areas of physics found their explanation. Also quantum mechanics had a very significant impact on the development of mathematics and mathematical physics. Today quantum mechanics is one of the keystone parts of theoretical and mathematical physics.

Vladimir Losyakov 
63 per term

MA060332  
Laser Spectroscopy (Term 1B4)
Spectroscopy is a science of studies of the quantum objects using the light. Before the laser era, its methods were limited to the spectroscopies of emission, absorption, and Raman scattering. The subject of the present course is not so much an improving, using the lasers, performance of the classical approaches (although this also is mentioned) but rather learning the new (more than a dozen) methods that have become possible only due to the appearance of the lasers. The course provides knowledge of the fundamental processes in spectroscopy as well as the methods allowing one to solve the problems that require (i) ultrahigh sensitivity, (ii) ultrahigh selectivity, (iii) ultrahigh spectral resolution, and (iv) ultrahigh temporal resolution. As an elective, the effects of quantum interference are considered such as coherent population trapping, the Autler–Townes effect, electromagnetically induced transparency, lasing without inversion, and more.

Alexander Makarov, Alexey Melnikov 
61.5 per term

Options  MA060212 
Machine Learning for Wireless Communication
This is a machine learning application course, intended to familiarize students with modern algorithms of the 5G wireless communication system and their implementation over Machine learning (ML). Within a few years, ML has become a prominent and rapidly growing research field among wireless communications both in academia and industry. The application of ML to wireless communications is expected to deeply transform wireless communication engineering in a few years. ML brings along a methodology that is datadriven and research in the field of ML for 5G is still largely in an exploration phase. In this course, we analyze the most promising applications of ML in the 5G system and propose students to realize some of them in Matlab or Python using the reallife data and stateofart algorithms we provide.
This course covers the following topics: Machine learningbased feature extraction for channel estimation, and MIMO detection 
Andrey Ivanov, Dmitry Yarotsky 
3  MA030413  
Machine Learning in Chemoinformatics
Deep learning achieves remarkable results in many fields, including life sciences. This course is made for students, that ready to apply their skills to scientific applications, such as molecular design and drug discovery. Molecules play vital roles in our organism, constantly interacting with each other and serving all the functionality, that we have as the human beings. Prediction of molecular properties, as well as design of molecules with target properties, are highly important problems, that still need to be addressed. Complex and rich nature of molecules allow to represent them as sequences, graphs, 3D objects, or highdimensional descriptors, and to apply numerical methods in order to solve open problems in chemoinformatics. Rapid accumulation of molecular data opened gates for machine learning to be applied for such representations, and to derive powerful prediction models that outperform empirical methods.
During this course students will be introduced with open problems in chemoinformatics and with stateoftheart machine learning methods attempt to solve these problems. Particularly students will practice deep learning, including 3D convolutional neural networks and generative adversarial networks, for drug discovery and molecular design problems. The course includes three theoretical lectures, that cover basics of molecular structures, such that no prior knowledge of structural chemistry or biology is required. Seminars are python coding sessions, where students apply machine learning pipelines to derive prediction models. The end of the course comprises final project aimed to solve chemoinformatics problem of choice using machine learning. 
Petr Popov  3  MA030364  
Master Your Thesis in English (Term 78)
The key to efficient professional communication is the ability to convey ideas clearly, coherently and correctly both orally and in writing.
The Course offers concise and practical guidelines for writing and defending a Master Thesis at Skoltech. The course focuses on the main parts of the Thesis in terms of structure, vocabulary and grammar, and their transformations for a presentation with slides. Students will develop a conscious approach to own writing and presentations through thorough analyses of the best authentic examples combined with intensive writing and editing practice. The ‘processforproduct’ approach teaches the students to write – use (peer) reviewer’s advice – revise/edit – repeat, and creates linguistic awareness needed to avoid the typical pitfalls. The Course is offered in two modules which gradually build on the necessary writing and presentation skills. 
Elizaveta Tikhomirova 
31.5 per term

Extra  MF030003 
Master Your Thesis in English 1 (Term 78)  Anastasiia Sharapkova 
31.5 per term

Extra  MF030003ls 
Methods of Enhanced Oil Recovery
Over onehalf of the original oilinplace remains in the reservoirs as primary and secondary recovery techniques have its technological and economic limitations. Major reasons are:
• heterogeneity of the reservoirs; • unfavorable fluid properties; • inefficient nature of the displacement process; economic constraints. A better understanding of the reservoir fundamentals and the important variables that influence the recovery process can enhance oil recovery. This course presents a comprehensive summary of chemical, miscible, and thermal enhanced oil recovery processes. The course presents the subject material with a clear focus on developing and producing the reservoir efficiently, energies available within the reservoir, realizing technical benefits and application limitations of the various enhanced oil recovery methods. 
Alexey Cheremisin  6  MA060117  
Modern Applications of Information Theory
The aim of the course is to explain modern ideas and concepts of information theory, as well as to present the emerging usecases.
The main focus of the course are the topics on the border of information theory, communications and machine learning, in particular (a) graphical models and iterative decoding; (b) deep neural network (DNN) based data compression; (c) DNNbased channel decoding; (d) information theory based analysis of DNNs and information bottleneck; (e) Massive random access in 5G/6G and interconnection to the compressive sensing problem. 
Pavel Rybin  3  MA030414  
Modern Dynamical Systems (Term 34)
Dynamical systems in our course will be presented mainly not as an independent branch of mathematics but as a very powerful tool that can be applied in geometry, topology, probability, analysis, number theory and physics. We consciously decided to sacrifice some classical chapters of ergodic theory and to introduce the most important dynamical notions and ideas in the geometric and topological context already intuitively familiar to our audience. As a compensation, we will show applications of dynamics to important problems in other mathematical disciplines. We hope to arrive at the end of the course to the most recent advances in dynamics and geometry and to present (at least informally) some of results of A. Avila, A. Eskin, M. Kontsevich, M. Mirzakhani, G. Margulis.
In accordance with this strategy, the course comprises several blocks closely related to each other. The first three of them (including very short introduction) are mainly mandatory. The decision, which of the topics listed below these three blocks would depend on the background and interests of the audience. 
Alexandra Skripchenko, Sergey Lando 
63 per term

MA060257  
Molecular Neurobiology (Term 34)  Philipp Khaitovich 
63 per term

MA060397  
Multiphase Flows in Pipes
Course is focused on modeling and analyzing a number of transport phenomena accompanying transport of multiphase flows through pipes, mainly in application to hydrocarbon production.
In application to petroleum engineering, modeling is required to properly evaluate risks and identify hydrocarbon production strategy. The major topics, which will be considered: oil/water flows, emulsion formation, asphaltene deposition, wax deposition, turbulent drag reduction. Practicing engineers, trying to model these processes, frequently experience significant difficulties due to both absence of reliable modeling approaches and limited field/experimental data. Clear engineering approaches to modeling these complex processes will be given and critically discussed. 
Dmitry Eskin  3  MA030292  
Neural Natural Language Processing
The course is about neural models for natural language processing. The new generation of neural networkbased methods based on deep learning has dramatically improved the performance of a wide range of natural language processing tasks, ranging from text classification to question answering. The course covers the basics and the details of successful models and methods for natural language processing based on neural networks, starting from the simple word embedding models, such as word2vec, all the way to more sophisticated language models, such ELMo and BERT. Besides, the course contains a small introduction to basic NLP methods. The course involves a substantial practical component with a number of practical assignments.

Alexander Panchenko  3  MA030361  
Neuromorphic Computing
The program of the course is designed to explore the frontiers of neuromorphic computing and artificial neural networks. We discuss advanced simulation tools for indepth inspecting the full potential of novel scalable architectures for neuromorphic engineering. In the framework of the course, we address a central and vital pillar in the design and control of scaledup processing arrays. In particular, understanding the general principles of scalability and optimization. After completing the course the students are supposed to be familiar with
(i) Principles of reservoir and stochastic computing and their practical implementation, (ii) Architecture of a neuromorphic processing system based on memristor arrays and validation of its performance. The course is multidisciplinary in nature, combining aspects of computer science and algorithm development with the deep mathematical understanding by means of stateoftheart analytical and numerical methods. 
Dmitry Yudin  3  MA030407  
Numerical Simulations of Quantum ManyBody Systems  Konstantin Tikhonov  3  MA030385  
Omics Data Analysis
An avalanche of ‘omics data is coming from different sources: transcriptomics, epigenomics, lipidomics, metabolomics. A thorough analysis of such largescale biological data sets can lead to the discovery of important biological insights on mechanisms of cell and organ functioning, and to the identification of small subsets of molecules (a ‘molecular signature’) to explain or predict biological conditions. The course will discuss general concepts of bioinformatics analysis of various types of ‘omics data and will provide examples of their successful application for solving a wide range of biological problems. The students will not only learn the best analysis practices suitable for each data type but, importantly, understand why each analysis step is necessary, what is the logic of the whole data analysis concept, which controls are essential, etc.
The chapters of the course will include: The course will end with the Final Project on the integration of different data types produced to answer the same biological question. The will be two groups of students: MSc and PhD students. While both groups will be attending the same lessons, PhD students are required to do more work to get the same grades as MSc students. In each practical task, homework, and exam, there will be additional tasks marked with an asterisk symbol. These tasks will be required to get the full grade for PhD students, but not for MSc students. Also, there will be final projects of increased complexity designed for PhD students, and more analysis will be expected from them on the final projects. 
Ekaterina Khrameeva  6  MA060061  
Omics Technologies
Omics technologies include different data intensive disciplines dedicated to the molecular profiling of various natural or biological systems: genomics, transcriptomics, proteomics, metabolomics, lipidomics, petroleomics. This course will be mainly focused on the mass spectrometry based techniques refereeing genomics to the special live science courses: Instrumental methods in Molecular Biology (T. Zatsepin) and Analysis of ‘omics data (E. Khrameeva). The base laboratory of the course is the Omics thechnology and Big Data laboratory (C. Borchers, supported by Megagrant).
The course will cover wide range of mass spectrometry techniques used for ion generation, separation, detection, data processing and interpretation. The course will teach the theoretical fundamentals required for choosing of the instruments and methods for measuring mass spectra of biological samples. The course will cover big data processing and machine learning approaches used for the biomarker discovery and tissue imaging. After successful completion of this class, students will acquire the initial knowledge of the operational principles and design of different mass spectrometers, different method of protein, peptides, lipids and metabolite molecule identification, different fragmentation methods for primary and secondary structure determination, methods of quantitative determination of proteins, lipids, metabolites and small molecule in physiological liquids. 
Evgeny Nikolaev  6  MA060360  
OneDimensional Quantum Systems (Term 34)
In the framework of the course, quantum systems (fieldtheoretic and discrete) in one spacial dimension, and some their classical statistical mechanics counterparts are discussed. The scope of systems includes sineGordon and Thirring model, O(n) sigma model, Heisenberg chain and sixvertex model, Kondo problem. We consider several techniques to obtain exact results for these systems, including operator product expansions, bosonfermion correspondence, YangBaxter equation, different versions of Bethe Ansatz.

Michael Lashkevich 
63 per term

MA060276  
Optical Communications (Term 34)
Communication is an important part of our daily life. The communication process involves information generation, transmission, reception and interpretation. As needs for various types of communication such as voice, images, video and data communications increase demands for large transmission capacity also increase. This need for large capacity has driven the rapid development light wave technology; a worldwide industry has developed. An optical or light wave communication system is a system that uses light waves as the carrier for transmission. An optical communication system mainly involves three parts: transmitter, receiver and channel. In optical communication transmitters are light sources, receivers are light detectors and the channels are mainly waveguides (e.g. optical fibers) or free space.

Franko Kueppers, Arkady Shipulin 
63 per term

MA060157  
Pedagogical Experience  Dmitry Artamonov  3  DE030005  
Planning Algorithms in Artificial Intelligence
Planning is the process of deciding which action to take in order to achieve some goals. This course will study planning and decision making under the scope of Artificial Intelligence, that is, we will mostly focus on algorithms that calculate the actions to take by an agent.
The course will cover a wide variety of planning problems, such as discrete planning, continuous planning, decisionmaking, planning under uncertainty, learningbased, etc. This diversity corresponds to the main objective of the course: provide a solid understanding to the student to successfully apply different planning techniques into a large variety of problems, including robotics, controls, manufacturing, drug design, computer graphics, and aerospace applications to name a few. This course is the first step into more advanced courses offered in Skoltech, such as Reinforcement Learning and more to come related to action in AI. The evaluation will consist of problem sets, related to seminar material prepared in class plus a final group project. 
Gonzalo Ferrer  3  MA030420  
Plant Biotechnology lab (Term 34)  Eugene Lysenko 
63 per term

MA060331  
Plant Genetics
This course will highlight several topics in plant genetics, with a focus on the plant genome and the mechanisms leading from the gene(s) to the phenotype. Plant genetics is often stereotyped as something outofdate, “mossgrown”. This is grossly unfair: on the contrary, in the past 1020 years it is at the peak of new discoveries. Advances in DNA sequencing, especially NGS, and the methods of genome transformation, boosted the development of this field. The course will combine lectures and seminars. The seminars will be held in the journal club format, where students will read and then discuss papers reporting important advancements in plant genetics and genomics.

Maria Logacheva  3  MA030399  
Plant Molecular Biology lab (Term 34)  Eugene Lysenko 
63 per term

MA060330  
Power Markets and Regulations  Janusz Bialek, David Pozo 
6  Sector  MB060002 
Practicum in Experimental Physics
This course assumes mastering in certain experimental techniques in physics, including a practical work with experimental setups. The course is practically oriented, with small share of lectures. Students will have an opportunity to conduct individual research project and be familiar with unique stateoftheart equipment.
The work can be starteded in Term 4, or can be continued after participation in Term 2. For SkoltechMIPT net program, both Term 2 and Term 4 are obligatory from MIPT side, but can be substituted with other courses in frames of individual MIPT plan. 
Valery Ryazanov  6  Options  MA060208 
Quantum Field Theory (Term 34)
At present time Quantum Field Theory (QFT) is the main theoretical tool used for the description of the phenomena occurring in the microworld. Examples include interactions between elementary particles, hadron structure and so on. At the same time, QFT methods are widely used in all areas of modern theoretical physics such as condensed matter physics, statistical mechanics, turbulence theory and others. Moreover, the creation of QFT has stimulated the development of many modern areas of mathematics.
The course is aimed at the study of the basic ideas and methods of QFT, as well as the discussion of its applications in various areas of modern theoretical and mathematical physics. Topics include quantization of scalar and gauge theories, path integral approach, perturbative expansions and Feynman diagrams, (1+1) dimensional exactly soluble models and some other ideas of modern science. 
Andrei Semenov 
63 per term

MA060316  
Quantum Integrable Systems (Term 34)
The course is devoted to quantum integrable systems. The history of quantum integrable systems starts from 1931 when
H.Bethe managed to construct exact eigenfunctions of the Hamiltonian of the Heisenberg spin chain with the help of a special substitution which became famous since that time (ansatz Bethe). In one or another form this method turns out to be applicable to many spin and fieldtheoretical integrable models. From the mathematical point of view, Bethe's method is connected to representation theory of quantum algebras (qdeformations of universal enveloping algebras and Yangians). Here is the list of topics which will be discussed in the course. – Coordinate Bethe ansatz on the example of the Heisenberg model and – Bethe ansatz in exactly solvable models of statistical mechanics – Calculation of physical quantities in integrable models in thermodynamic – Bethe equations and the YangYang function, caclulation of norms of Bethe – Quantum inverse scattering method and algebraic Bethe ansatz, quantum Rmatrices, – Functional Bethe ansatz and the method of Baxter's Qoperators, functional The knowledge of quantum mechanics and statistical physics for understanding of 
Anton Zabrodin 
63 per term

MA060315  
Quantum Mesoscopics. Quantum Hall effect (Term 34)
The course of lectures consists of two roughly equal parts. The first part begins with an account of the physics of twodimensional electrons in a perpendicular magnetic field and attempts to explain the phenomenon of an integer quantum effect for shortrange and smooth random potentials. The presentation in this part is supposed to be quite accessible to students familiar with quantum mechanics and diagram technique. In the second part of the course, the fundamentals of the fieldtheoretical description of the phenomenon of an integer quantum Hall effect in a shortrange random potential are presented. To understand the material of the second part, students need to know the methods of functional integration and quantum field theory.

Igor Burmistrov 
63 per term

MA060278  
Quantum Optics
“Quantum optics, the union of quantum field theory and physical optics, is undergoing a time of revolutionary change” [Marlan O. Scully and M. Suhail Zubairy “Quantum Optics”, Cambridge University Press].
Quantum optics studies interactions between matter and the radiation field where quantum effects are important. The fundamental interest in quantum optics is connected with conceptual foundations of quantum mechanics, with nonclassical effects such as quantum interference and entanglement, photon antibunching and squeezing, as well as with numerous applications in precise measurements, protected information transfer, etc. This introductory course includes the following topics: quantization of electromagnetic field, Fock (number) states of the field, Lamb shift, Casimir effect, coherent states of the field, interaction of photons with atoms, Rabi and Jaynes – Cummings models. Dressed states. Dicke super and subradiation, quantum coherence and correlation measurements, quantummechanical detector of photons, singlephoton interferometer, quantum beam splitter, Young’s type interferometer, Michelson’s stellar interferometer, physics of HanburyBrownTwiss interferometer, nonclassical states of light, squeezing in nonlinear optical processes, bunching and antibunching of photons, “Schroedinger’s cat” states. 
Vladimir Yudson, Yulia Vladimirova 
3  MA030161  
Quantum Theory of Radiation and Quantum Optics (Term 1B4)
The main goal of the course is to study by students basic physical principles, main quantum electrodynamical (QED) phenomena and mathematical apparatus of quantum electrodynamics and quantum optics. Students must know theory and experimental data on interaction of radiatiation with matter. Particularly will be discussed: quantum theory of electromagnetic field, problem of phase in QED, coherent and squeezed states, relativistic quantum theory of electrons and positrons, Klein paradox, diagram technique,
divergences and renormalization of mass and charge of electron, Lamb shift, cavity quantum electrodynamics (including last achievements), dynamical Casimir effect, basics of united theory of electromagnetic and weak interactions etc. 
Yuri Lozovik 
61.5 per term

Options  MA060314 
Quiver Representations and Quiver Varieties (Term 34)
The theory of quivers is one of the central topics in various fields of modern mathematics and mathematical physics, such as algebraic geometry, representation theory, combinatorics, quantum field theory, integrable systems. The theory has lots of beautiful and deep theorems and is very popular due to a huge number of applications, including McKay correspondence, instantons and ADHM construction, geometric realization of the KacMoody Lie algebras. Many of the recent results and applications of the theory of quivers are based on the quiver verieties, introduced by Hiraku Nakajima 20 years ago. The course will cover the basic material on the structure theory of quivers and their representations, such as path algebras, Gabriel's theorem, Hall algebras, preprojective algebras and AuslanderReiten quivers. Based on the general theory of quiver representations we will discuss the definition of the Nakajima quiver varieties and several explicit examples and applications. The course is aimed at the graduate students or advanced bachelor students. The basic knowledge of algebraic geometry, differential geometry, and the theory of Lie groups and Lie algebras is expected.

Evgeny Feygin 
63 per term

MA060425  
Research (Term 58)  Mikhail Skvortsov 
61.5 per term

MA060432  
Research Methodology: Bioinformatics
The course consists of two main components: discussion of typical approaches and problems common to different areas of bioinformatics and work with bioinformatics texts, such as writing papers, responding to reviewer comments, reviewing papers, writing grant proposals, etc. Both parts will be based on actual cases; in the first stream the students will analyze particular problems and apply generic rules (or spot inconsistencies in application of these rules), in the second stream the students will review actual papers and analyze reviews by others, write and review grant proposals, analyze published retractions and the reasons for them, and so on. In particular, we will systematically analyze bioinformatics papers on SARSCoV2.

Mikhail Gelfand  3  DA030404  
Research Methodology: Molecular Biology Seminar
Main topic of term2 seminar will be "CRISPR – the beginnings"
For each class, there will be a paper that two people will present to the rest of the class. We will go down to the details of experiments – how things were done and what do the data/figures really show, so be prepared to answer indepth questions. Presenters will start by stating the name of the paper/main authors and telling the take home message of the paper – why it is signficant, what problem it solved. Then they will proceed to the actual work. If there are methods/results mentioned in the paper that refer to prior work, you shall be prepared to answer questions about it too. The audience is supposed to read the paper being discussed beforehand and participate in discussions. To pass, one would need to present a paper at least once during the module and actively take part in discussions of other papers. One absence is allowed no questions asked. Additional absences when unexplained will be a cause for nopass grade. There will be a few home assignments. They must be submitted in time, typed–not written up–and done professionally (written in good language, be concise and free of spelling errors – consider them as part of academic writing exercises). It is gonna be fun – students tend to like the seminar and its atmosphere Dear students, Please note that the final list of participants will be selected by prof. Severinov after registration closes. 
Konstantin Severinov  3  DA030102ls  
Research Methodology: Space Center Seminar (Term 14)
The seminar will cover current topics in the space domain: latest news, discoveries. Also planned that all PhD students and some Master students will present their research. External lecturers will be invited regularly to focus on the main applications of space technologies: science, telecommunication, navigation and remote sensing. Aspects of space technologies will also be discussed: structures, software, attitude determination and control systems, on board computers, communication system power supply systems and others. The seminar will be offered in English.

Anton Ivanov 
30.75 per term

DA030102es  
Research Seminar "Advanced Materials Science" (Term 28)  Keith Stevenson 
30.5 per term

DA030302  
Research seminar "Energy Systems and Technologies" (Term 24)
This research seminar is the general meeting for faculty, researchers and master and PhD students of Energy Systems programs. The seminar takes place every week during Terms 2(6)3(7)4(8).
Master students must attend the seminar at least for one academic year but welcome to attend during two years. PhD students are welcome to attend the seminar during all years of studies but can gain no more than 6 credits in total. The seminar consists of faculty lectures, invited lectures of top scientists in their research field as well as students’ reports on their own or examined papers. To PASS the course and gain 3 credits per academic year the student must fulfill all three requirements: 1. Attendance: > 2/3 of seminars. 2. Presentation. Depending on the status: 3. Evaluation. Filling in the Online feedback form. The core of the selfstudy activity will be preparation to the talk that is comparable to project implementation (a significant part of many regular courses). The students are expected to assign at the beginning of Term 2/6 and may drop the seminar till the beginning of Term 3/7 while credits are provided in Term 4/8. 
Elena Gryazina 
31 per term

MA030386  
Research seminar "Modern Problems of Mathematical Physics" (Term 14)
Course "Modern problems of mathematical physics" is a student seminar, so participants are expected to give talks based on the modern research papers. Current topic of the seminar can vary from time to time: now it is devoted to the study of N=2 supersymmetric gauge theory and its links with random matrix models, ABJM theory, localization, complex curves, and integrable systems. Other topics that were already covered, or can be covered in the future, are: classical integrable equations, complex curves and their thetafunctions, quantum integrable models (quantummechanical and fieldtheoretical), models of statistical physics.

Pavlo Gavrylenko 
61.5 per term

DA060268  
Research seminar "Modern Problems of Theoretical Physics" (Term 14)
Research seminar "Modern Problems of Theoretical Physics" is supposed to teach students to read, understand and represent to the audience recent advances in theoretical physics. Each student is supposed 1) to choose one of recent research papers from the list composed by the instructor in the beginning of each term, 2) read it carefully, 3) present the major results of the paper to his/her colleagues during the seminar talk, 4) answer the questions from the audience about the content of the paper. The papers in the list are selected, normally, from the condensed matter theory and related fields, like: physics quantum computing, statistical physics, etc. The papers to the list are usually chosen from most competitive physics journals, like Nature Physics, Science, Physical Review Letters, Physical Review X and others.

Mikhail Feigelman, Konstantin Tikhonov 
61.5 per term

DA060319  
Review of Materials and Devices for Nano and Optoelectronics (Term 34)
The lectures are presented by the scientists working actively in various directions of nanoelectronics and optoelectronics in Russia and abroad. Seminars assume the discussion of recent original papers in the area (including superconducting electronics and spintronics, terahertz waves technology and applications, quantum coherent systems (qubits), single electron devices). The classical papers presenting a physical basis for devices operation will be also considered. The papers are distributed in February. Each student is expected to report two papers during the period FebruaryMay.

Valery Ryazanov 
63 per term

MA060206  
Safety and Robustness Aspects of Artificial Intelligence Applications
AIbased applications occupy ever more areas of human activity. The related machine learning methods have been enjoying a new momentum with the broadening application of deep and convolution artificial neural nets. TensorFlow played an important role in this trend as it greatly eased implementation of deep neural nets. Despite these positive trends, there are still gaps in AI methodologies, primarily related to safe operation. When it comes to, say, image classification on a web platform, system safety might be not in the foreground, but it is indeed in an autonomous car, a robot or unmanned aircraft or ship. The Stanford Center for AI Safety has recently raised these concerns in a respective white paper. It seems we are standing at an emerging interconnection of various disciplines that may come handy in machine learning for guaranteeing stability, robustness and user certificate satisfaction.
In this course, we tackle these challenging questions by looking at neural networks from an interdisciplinary point of view. Machine learning is traditionally concerned with the neural network performance, say, in terms of weight convergence and predicting ability. In system theory, we might look at the neural network learning as being a dynamical plant with welldefinable properties, such as stability or inputtooutput robustness. Or, we may interpret it in a formal setting of some axiomatic system and pose such questions as: "Does the network produce correct output provided with so or so input?". In faulttolerant control, in turn, one might want to detect, e.g., an activation function fault and remedy it. And so on … Thanks to view from various perspectives, you will not just expand your knowledge of AIbased methods, but enrich and broaden your understanding of neural network functioning, as well as get better fit for the new generation of safe AI. 
Pavel Osinenko  3  MA030419  
Selected Topics in Energy: Physical, Chemical and Geophysical Challenges (Term 24)
The course provides an introduction to the modern topics related to fundamentals of exploration of energy resources, energy generation, storage, conversion and use. It identifies the corresponding practical challenges to be addressed at the fundamental research level and familiarizes the students with the stateoftheart approaches, methods and techniques in use in related scientific areas. The course seeks to emphasize and maintain interdisciplinary nature of the energyrelated topics, in particular, combination of micro and macroscopic approaches of geophysics, mechanics and chemistry in hydrocarbon exploration and development, relation between the physical and chemical processes of energy generation and conversion, integration of physical, chemical and mechanical approaches to perspective materials (physical and chemical synthesis, micro and macroscopic characterization, structureproperty relations, etc.) and related theoretical methodologies. These interdisciplinary links are mostly demonstrated by horizontal knowledge exchange among the students reporting and discussing practical examples from their own research field or from modern review or research publications. Topical lectures are included for further exploration of these links. The secondary aim of the course is the development of presentation skills (oral and writing), as well as scientific peerreview experience. The seminar format chosen for most activities allows students free exchange of knowledge and ideas, broader vision of their research projects and methodologies, better assessments of their own research skills and demands for further education.

Alexei Buchachenko 
62 per term

DA060106  
Sensors and Embedded Systems for IoT
This module will give a wideranging introduction to sensors and embedded systems in the scope of Internet of Things (IoT) paradigm. The module aims at providing full support to the nonengineering students with a series of carefully constructed concepts and exercises. It starts with setting the whole picture of IoT and its requirements for sensors and embedded systems. Then it introduces basic principles and simple projects, and moves towards more advanced IoT system design. Finally, the module will make overview of targeted applications including SmartX, Oil & Gas industry, wearables and medical applications.

Andrey Somov  6  MA060235  
Smart Grids
Power systems around the world are undergoing a period of unprecedented change. A typical 20th Century power system was characterized by unidirectional flow of power from a limited number of large controllable power stations to a highly predictable demand. There was no energy storage so that at any time generation had to be equal to demand and the infrastructure utilization rates were low (about 55% for generation, 30% for transmission and even lower for distribution). Generally planning and controlling such a system was relatively straightforward as it was based around principles of deterministic hierarchical control, usually based on (N1) reliability criterion.
On the other hand the emerging 21st Century power system is characterized by bidirectional flows between a very large number of uncontrollable and stochastic generators (usually, but not always, renewable ones such as wind or solar) and stochastic and often poorlypredictable demand. Demand ceases to be predictable as it consists of consumers equipped with smart meters and wind/solar generators hence possibly becoming net generators – socalled prosumers. Increased penetration of energy storage, both stationary and mobile due to a takeup of electric vehicles, offers buffering possibilities in dispatch (generation does not have to be equal to demand at any time). Controlling such a power system is the main research challenge in power systems and it is made possible by latest advances in ICT (Information and Control Technology), communication networks, Internet, GPS, sensors, etc. However it requires new tools and methodologies, the Smartgrid course will give the basis of this new grid scenario. 
Federico Martin Ibanez  6  MA060056  
Space Sector Course  Anton Ivanov, Tatiana Podladchikova 
6  STE  MB060003 
Superconducting Quantum Technologies
This course provides an overview of the rapidly developing field of physics of superconducting quantum systems. The course gives an introduction to basic phenomena of onchip quantum optics in the microwave range, explain the quantum mechanical approach to superconducting circuits, study the interaction of electromagnetic waves with artificial atoms and provide examples of theoretical understanding and experimental realizations of these effects. Prior knowledge of quantum theory at the level of braket notation and quantum evolution is assumed. Knowledge of superconductivity is not required.

Oleg Astafiev  6  MA060340  
Technological Innovations: from Research Results to a Commercial Product  Pavel Dorozhkin  3  E&I  MC030028 
Technology Entrepreneurship: Advanced
The course expands “Technology Entrepreneurship: Foundation” class towards the topics related to primary market research and customer discovery, product prototyping and testing with users, marketing, business modeling, investments for startups, etc. It is designed to help students to master practical skills of entrepreneurship and transfer their own early stage projects/ideas into viable business concepts, validated prototypes/products, and, finally, fundable companies. This is an active learning course. It deals with the firsthand experience of all the pressure and demands of the real world in an early stage technological startup. Students will work as a team and deal with market/technology uncertainty. They will get out of the classroom to learn from the marketplace and to check if anyone would use/pay for their product. Finally, based on market feedback students will rapidly iterate their products into something customers would really use and buy. As a framework for the course we use the “battle proven” approaches as “Disciplined Entrepreneurship” (Bill Aulet, MIT) and “Customer Development” (Steve Blank, UC Berkeley & Stanford). One of the course final deliverables will be the project description prepared in accordance with Skolkovo Foundation application form requirements.
Course benefits: 
Alexey Nikolaev  3  E&I  MC030015 
Technology Planning and Roadmapping: Advanced
• Technology Planning and Roadmapping: Advanced (TPR:A): this course represents the practical application of the tools taught in TPR:F. It provides students the opportunity to practice hands on the real issues that arise in implementing a TPR system in industrial organizations, and to develop an actual technology roadmap in class teamwork. The best technology roadmaps coming from different class editions may be published online or in international peerreviewed venues, with students as lead authors (Scopusindexed conferences or journals). TPR:A is about using the TPR system to explore a cuttingedge technology area of choice of the class, among those aligned with major trends occurring worldwide across different technology sectors of relevance to Skoltech (Biomed, Energy, IT, and Space). The main deliverable of TPR:A is a groupbased technology roadmap report. Students will develop in teams a sectorwide technology roadmap, to be later presented as a report.

Alessandro Golkar  3  E&I  MC030018 
Theoretical Foundations of Data Science
In this course, we introduce the forefront of modern research in data science and familiarize Ph.D. students with state of the art in those areas. In particular, we introduce cornerstone subjects that are not commonly discussed in undergraduate or graduate Machine Learning classes. This course is intended to serve as an introduction to the basics of everyday industrial software engineering. Also, this course explores extensively four novel areas in Machine Learning, namely Causality, Sequential Data, Geometric Computer Vision and Reinforcement Learning.
Over multiple weeks, we will investigate how these methods and algorithms can be used for analyzing scientific data, social networks or timeseries data, mining sequences, carrying out text/web analysis, topic modeling, and pattern mining. We explore how these concepts are applied for dimensionality reduction and manifold learning, combinatorial optimization, relational and structured learning, classification and regression methods, semisupervised learning, unsupervised learning including anomaly detection and clustering, kernel methods, compressed sensing and sparse modeling, Bayesian methods, deep learning, hyperparameter, and model selection. The course aims to bring all students on the same page regarding the nature and orientation of stateoftheart work in their field so that they acquire both depth and breadth of knowledge. 
Evgeny Burnaev  6  DA060140  
Thermal Spray Coatings (Term 34)
Thermal spray technology provides a costeffective functional surface solution for many applications requiring resistance to wear, heat, and corrosion. This practicallyoriented course is intended to familiarize graduate students with an understanding of thermal spray processing science and frontline research topics, with attention to latest development and innovations in the field. The second purpose of this interdisciplinary course is to give the students technological/engineering perspectives of thermal spray applications and practice.
Students’ key learning objectives: 
Igor Shishkovsky 
63 per term

MA030356  
Thermodynamics and Transport at Nanoscale
The course introduces students to basic principles of thermodynamics and transport in “small systems, that is, the system whose size is comparable to the size of its major elements (be those molecules, micelles, polymer coils, etc). It covers small droplets, bubbles and crystals, stability of thin films, adsorption and deformation in nanoporous materials, stability of nanocolloids and nanocomposites, as well as transport and flows in microand nano porous networks. In the process of studies, the students will also learn/reiterate the basics of interfacial thermodynamics, adsorption, wettability, spreading as well as the basics of transport of ionic and nonionic compounds in confined media. The lectures, seminars, homeworks and the final project will give practical example of calculations for all major classes of nanomaterials: nanoparticles and nanocomposites, microporous crystals, ordered and disordered mesoporous solids, and, finally nanostructured polymeric materials.
The course will be useful to all students willing to improve their understanding of natural (e.g. mineral oil) and manmade colloids, such as suspensions, emulsions and foams, as well as natural and synthetic porous materials. "Lectures" in the schedule refer to approximately 3h "windows" they will are not necessary scheduled as such, but will spread out and intermitted by seminars / recitations / HW and project discussions 
Alexey Vishnyakov  3  MA030288  
Transgenic Models in Drug Discovery  Yuri Kotelevtsev  6  MA060398  
Virology
The course consists of two parts: Molecular Virology (Term 3) and Introduction to the Medical Virology (Term 4). In the first part, the structure of viruses, their genetics as well as replication and transcription strategies will be explained. These aspects are crucial for understanding the second part of the course, which focuses on mechanisms of how viruses act on the whole organism and how organisms react to viral infection. Such topics as an immune response against viruses, types of viral infections, vaccines and antivirals will be covered in the second part of the course. Throughout the whole course, the world's most notorious pathogens such as HIV, Ebola, Zika and Influenza, will be discussed in depth.
Lectures are based on the Virology course led by professor Racaniello at the University of Columbia with his kind permission. Lectures will be combined with seminars at which the papers important in the field will be discussed. After the completion of the course, students will know the history of virology, its current problems as well as directions for further development. 
Maria Sokolova  6  MA060374  
Virtual Reality and Haptics
VR and Haptics technologies are booming in the world. Students of the course will learn how to make 3D environment and digital twins. They will create the VR copy of the robot, control its motion with tracking system, and literally touch the future technologies with the most recent electrotactile display provided by UEC (Japan). They will learn how to program ESP microcontrollers, digital filters, and to write the software for tracking the user fingers, arms with motion capturing systems. They will be taught the neuroscience of the human sense of touch, principles of haptics technologies and tactile displays for highly immersive VR, HRI, and HCI. The experimental design with ANOVA test will be presented. At the end of the Lecture, the students will have the chance to participate in the scientific content of the most prestigious conference in CG and novel technologies ACM Siggraph 2020 (Core A*). The invited speakers will be from such companies as Unity, NVIDIA, AntiLatency, Native Robotics (startup of ISR Lab.), Tsuru Robotics (startup of ISR Lab.), Sizolution (startup of ISR Lab.).

Dzmitry Tsetserukou  3  MA030378 
Course Title  Lead Instructors  ECTS Credits  Stream  Course Code 

Pedagogy of Higher Education  Magnus Gustafsson  3  DE030025 