Skoltech is an international graduate research-focused university that was founded by the group of world-renowned scientists in 2011. Skoltech's curriculum focuses on technology and innovation, offering Master's programs in 11 technological disciplines. Students receive rigorous theoretical and practical training, design their own research projects, participate in internships and gain entrepreneurial skills in English. The faculty is comprised of current researchers with international accreditation and achievements.
People have been intrigued by poisons since the beginning of time. Over thousands of years, poisons were used as a weapon, an escape from punishment and even as proof of eternal love.
Although virtually instant killers, poisons serve a noble cause by helping create effective painkillers and anesthetics. Medical scientists across the globe are busy studying the broad diversity of poisonous chemical compounds trying to grasp how they save or kill living cells.
What is a poison? What is the chemical structure of a poison? Which organisms use their deadly weapons and how do they do that? Can modern methods help recognize a poison? How can poisons help study the nervous system?
To get answers to these questions and learn more about poisons, join the online lecture by Maria Yarina, a biologist and a researcher at Skoltech.
Maria Yarina, a researcher at Skoltech, graduated from the Department of Biology at Lomonosov Moscow State University with a degree in mycology. The focus of her current research at the Gause Institute of New Antibiotics is the biologically active polysaccharides of basidiomycetes.
Physics Department, Carl von Ossietzky Universität Oldenburg The possibility to assemble two-dimensional materials to form vertical heterostructures held together by van der Waals forces has open unprecedented perspectives to tune the properties of materials at the nanoscale. The huge complexity arising from combining different materials and the exotic phenomena that can consequently manifest themselves calls for in-depth theoretical studies based on state-of-theart ab initio methods. Density-functional theory and many-body perturbation theory are ideally suited for this purpose. In this seminar, I will present recent results obtained in this framework on van der Waals heterostructures formed by encapsulating graphene into hexagonal boron nitride (h-BN) [1,2] and by interfacing the two transition-metal dichalcogenide monolayers ZrS2 and HfS2 [3]. In the first example, I will illustrate how the controlled intercalation of graphene between h-BN multilayers can significantly enhance light-matter interaction in the resulting heterostructure and lead to charge-transfer excitations in the visible region [1,2] as well as to an overall stacking-dependent character of the electron-hole pairs [4]. In the ZrS2/HfS2 heterobilayer, I will focus on the peculiar type-I level alignment, which, combined with the large hybridization between the two monolayers, gives rise to a non-trivial (de)localization of the electron and hole components of the exciton [3].
References
[1] W. Aggoune, C. Cocchi, et al., J. Phys. Chem. Lett. 8, 1464 (2017). [2] W. Aggoune, C. Cocchi, et al., submitted (2020); arXiv:2004.06031. [3] K.-W. Lau, C. Cocchi, and C. Draxl, Phys. Rev. Materials 3, 074001 (2019). [4] W. Aggoune, C. Cocchi, et al., Phys. Rev. B (R) 97, 241114 (2018).
The figure is taken from Ref. [1].
Place: The seminar will be given using Zoom platform. Please contact to get an invitation.
Ivan Oseledets, Skoltech professor of the Center for Computational and Data-Intensive Science and Engineering (CDISE), Anima Anandkumar, NVIDIA machine learning research director, Tom Gruber, Humanistic AI Founder, and Yva. ai Co-Founder & CEO David Yang will make a presentation “AI as a Masterpiece. How artificial intelligence sets the trends” at the Startup Village Livestream’20 virtual conference, the key Russian free technology event of the year, on May 21 at 6:20 p.m. Moscow time. Read more on https://startupvillage.ru/en/program/session/6
Maxim Fedorov, Skoltech professor and vice president for Artificial Intelligence and Mathematical Modelling, and Sergei Dutov, Business Development Director at Skolkovo Foundation, will make a presentation “Sustainable AI development. Skolkovo and Skoltech global initiatives” at the Startup Village Livestream’20 virtual conference, the key Russian free technology event of the year, on May 22 at 11:35 a.m. Moscow time. Read more on https://startupvillage.ru/en/program/session/129
New discoveries tend to generate hype. It has become a common habit to worry about excessive use of technology and succumb to the fear that it may disturb our lives. And the image processing technology seems to be the talk of the town…
Evgeny Burnaev, an associate professor at Skoltech, will go online to discuss machine learning and related topics. He will talk about algorithms underlying deep neural networks and how they can be used to process 2D images and 3D scans captured by unmanned vehicles’ lidars, smartphone cameras and medical scanners.
Evgeny Burnaev is an associate professor at the Skoltech Center for Computational and Data-Intensive Science and Engineering (CDISE). Evgeny holds a PhD degree in Physics and Mathematics and a Master’s degree in applied physics and mathematics from the Moscow Institute of Physics and Technology (MIPT). Before joining Skoltech, he directed the Laboratory of Data Mining and Predictive Modeling at the Institute for Information Transmission Problems of RAS (IITP RAS).
Evgeny participated in a variety of projects with Airbus, SAFT, IHI, Sahara Force India Formula 1 team and more. Currently, he leads the scientific group on Advanced Data Analytics in Science and Engineering at Skoltech. His research interests include the development of deep neural network training models and methods for predictive analytics and 3D computer vision tasks, including the processing of medical images.
Burnaev is the winner of the Moscow Government Award for Young Scientists in the “Data transfer, storage, processing and protection” category within the topic “Development of predictive analytics methods in the processing of industrial, biomedical and economic data”.
