Information Science and Technology

The Information Science and Technology program at Skoltech aims to train researchers working on computational approaches for science and technology problems, ranging from artificial intelligence and machine learning to modeling complex physical systems, as well as from computational engineering to analysis of complex image and textual data and large data analytics.

The graduates of the program are trained to perform original research in their chosen area and apply the results of their research in an industrial context. Students have numerous opportunities for collaborative research with faculty at leading international universities and industrial research labs in Russia and abroad.

Master of Science students in the Information Science and Technology program have the choice to follow one of the two main educational tracks:

The emphasis in the Data Science track is on learning state-of-the-art techniques of machine learning and data analytics (e.g. deep learning) for extracting useful information from large amounts of heterogeneous data (“big data”). The emphasis in the Computational Science and Engineering track is on computational methods intended for solving numerical problems arising from physical processes. In-depth education in one track can be complemented by elective education in  the other one.

Educational activities in each of the above tracks are strongly intertwined with the research activities at Skoltech Center for Computational Data-Intensive Science and Engineering (CDISE) and other centers of science, education and innovations (CREIs) in Skoltech, as well as jointly with their partners – leading national and international research and academic organizations.

The Industrial Immersion component of the Information Science and Technology program involves a set of faculty-supervised industrial placements and participating in short-term research projects of real interest to the partner companies.
The Information Science and Technology program further includes an Innovation Workshop, an Entrepreneurship & Innovation core course and elective innovation projects in later terms.

The choice of a track means that, by the end of the Master’s program, the student must complete basic courses specified by each track (see the above links) along with elective courses. In addition to the track-specific requirements, every student is required to satisfy Skoltech-wide requirements, which include a balanced mixture of elective courses, two Entrepreneurship & Innovation courses and an industrial immersion or internship. Elective courses may include specialized courses within the chosen track, supervised individual research, as well as courses not associated with a particular track.  Students are advised to broaden their horizons by selecting elective courses on the subjects different from their main area of study. For instance, they can take advantage of attending engineering courses and biomedical courses offered by other programs in Skoltech.

Students admitted to the program are expected to have a solid background in mathematics (multivariate calculus, linear algebra), and computing (proficiency in at least one commonly used programming language, knowledge of basic algorithms, data structures and computer architecture). Some background in natural sciences or/and engineering is recommended for the Computational Science and Engineering track.

The list of Skoltech staff affiliated with the Information Science and Technology Program includes: Mikhail Belyaev, Evgeny Burnaev, Mikhail Chertkov, Maxim Fedorov, Grigory Kabatianski, Panagiotis Karras, Stamatios Lefkimmatis, Viktor Lempitsky, Ivan Oseledets, Maxim Panov, Athanasios Polymeridis, Alexander Shapeev, Vladimir Spokoiny, Dzmitry Tsetserukou, Dmitry Yarotsky, Alexey Zaytsev and Andrii Zhugayevich.

External lecturers of Information Science and Technology courses (in the recent past or near future):

  • Quentin Paris (HSE)
  • Alexey Frolov (MIPT)
  • Alexander Gasnikov (MIPT)
  • Vladimir Selegey (ABBYY)

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