Mathematics, Computer Science, and Information Technology
Mathematics, Computer Science, and Information Technology
Doctor of Sciences in Physics and Mathematics, Research Professor at the HSE Faculty of Computer Science, Full professor of Computer Science at the Catholic University of Louvain
Strategic Academic Unit Structure and System
Mathematics, Computer Science and Information Technology Strategic Units falls into the first category of HSE Strategic Academic Units.
Management Committee (Heads of key units):
International Advisory Council:
- Pierre Deligne, Professor at the Institute for Advanced Study, Princeton, USA, Abel Prize Laureate 2013;
- Sergey Fomin, Professor at the Department of Mathematics of the University of Michigan, USA;
- Bernhard Ganter , Emeritus Professor of Mathematics at Technische Universität Dresden, Germany;
- Susanne Graf , Research Director at VERIMAG/CNRS, Université Grenoble Alpes, Grenoble, France;
- Ralph Kenna, Professor of Theoretical Physics at Coventry University, UK;
- Tetsuji Miwa, Full Professor at the Department of Mathematics of Kyoto University, Japan;
- Mark Novotny, Professor and Head of the Department of Physics and Astronomy of Mississippi State University, USA.
To build an ongoing research cycle and educational trajectory 'from fundamental mathematics via computer science to applications in information technologies and contemporary engineering' that will produce scholars, practitioners and researchers highly competitive at the national and international markets.
- Breakthrough research in the top globally evolving fields of study: algebraic geometry and mathematical physics, data analysis and machine learning, mathematical and computer modelling;
- Supporting research in the following interdisciplinary fields: number theory, representation theory and dynamical systems, mathematical logic and theoretical computer science, mathematical methods of optimization and stochastics, system and software engineering;
- Development of mathematical tools and computer technologies for use in social science, economics and humanities;
- Development of English-taught Master’s programs in mathematics and software engineering, implementation of educational programs in partnership with leading Russian and international research centers in fundamental mathematics and data science;
- Regular adjustment of educational programs’ curricula and teaching methods based on professional demands and the requirements of the IT labor market.
Main Anticipated Deliverables:
- New research areas: biological and medical informatics, neuromathematics, use of machine learning methods in social and humanitarian studies, operating systems and compilation technologies;
- World-class results in the study of the geometry of algebraic varieties in collaboration with Steklov Mathematical Institute; in data analysis with applications of the processing of experimental evidence produced by the Large Hadron Collider; in the area of information retrieval, computer vision and recommendation systems in partnership with Yandex;
- Practice-oriented model for educational programs based on the integrated interaction system 'faculties – research laboratories – academic institutes – high-tech companies', implemented in coordination with Yandex, the Institute for Information Transmission Problems (Kharkevich Institute) and the Institute for System Programming. This model, on the one hand, will ensure that recent academic achievements and technological solutions are used in the study process. On the other hand, the model facilitates the transfer of technologies developed by Stategic Academic Unit project groups and laboratories to the open market, with support from partner companies (Yandex, JetBrains, CROC, etc.);
- Bachelor’s and Master’s programs with an enhanced interdisciplinary component, such as Applied Mathematics and Informatics with exclusive concentrations in deep learning, neural networks, image and video analysis;
- Elective tracks at the undergraduate-master level and master-doctoral level, designed for students from different fields of study; for students of HSE doctoral schools in mathematics, computer science and technical sciences, a thesis topic should be related to Stategic Academic Unit’s current research or applied projects;
- The University’s international academic reputation has been evidenced by its entering the Top-150 in the QS Subject Ranking for Mathematics, the Top-300 in the QS Subject Ranking for Computer Science & Information Systems and the Top-200 in the ARWU Ranking for Mathematics.
Key Subdivisions and Associated Units:
- Faculty of Mathematics;
- Faculty of Computer Science;
- Moscow Institute of Electronics and Mathematics (MIEM);
- International Laboratory of Algebraic Geometry and its Applications;
- International Laboratory of Representation Theory and Mathematical Physics;
- International Laboratory of Theoretical Computer Science;
- International Laboratory for Intelligent Systems and Structural Analysis;
- Laboratory of Process-Aware Information Systems;
- Laboratory of Methods for Big Data Analysis;
- Laboratory of Mathematical Methods in Natural Sciences.
Grant Proposal (PDF, 692 Kb)
Roadmap (DOCX, 174 Kb)
Key Educational Programs and Their Development
Stategic Academic Unit is responsible for 6 Bachelor’s programs, 12 Master’s programs and 1 Specialty's program (about 3000 students, including more than 150 international students).
Stategic Academic Unit’s partnership and close collaboration with external organizations is a distinctive feature of its educational programs. Stategic Academic Unit partners with both academic institutes in fundamental mathematics and large IT companies. Experts from external organizations are involved in the development of programs and the teaching process, and students participate in research projects and do internships at partner companies.
Programs in fundamental mathematics are delivered in partnership with the Steklov Mathematical Institute, Lebedev Physical Institute, Kharkevich Institute, Leiden University, University of Tokyo, University of Luxembourg and Osaka University. Students take part in research projects on algebraic geometry, representation theory, mathematical physics and theoretical computer science.
- Undergraduate program in Mathematics (Academic Supervisor: Professor S.M. Khoroshkin, Doctor of Sciences) includes courses in fundamental mathematics and its application in physics, economics and computer science. The program offers a broad variety of elective courses and individually-designed study plans; the program attracts the best applicants in Russia. In 2015, 3 winners and 4 awardees at the final stage of the All-Russian Olympiad of Secondary School Students in Mathematics and 2 winners and 1 awardee in Physics were enrolled in the program. The passing score (on Russian Unified State Exam) in 2015 was 260 out of 300. After graduation, some students choose to continue their studies at leading international universities including MIT (3 undergraduate students entered MIT in 2015), СalTech, and ETH Zurich, while others immediately enter the workforce, taking jobs at the Central Bank of the Russian Federation, Bank of Moscow, Otkritie Bank, AT Consulting, SIBUR Holding, KMPG, and other organizations.
- Master’s program in Mathematics is delivered in English under the supervision of Professor Y.S. Ilyashenko, Doctor of Sciences. The program trains two kinds of specialists: prospective researchers in the field of mathematics and other exact sciences and prospective experts in knowledge-intensive applications.
- Master’s program in Mathematics and Mathematical Physics supervised by Professor I.M. Krichever, Doctor of Sciences, includes a block of courses in physics in addition to a broad selection of courses in mathematics. This enables students to acquire in-depth knowledge of fundamental models of contemporary theoretical physics and gives them an opportunity to seek employment at leading research centers in Russia and abroad.
Some programs in applied mathematics and informatics have been developed and are delivered in cooperation with Yandex. Students are engaged in research projects in machine learning, data analysis and theoretical computer sciences. Student project work is supervised by experts from Yandex, JetBrains, EMC and other partner companies.
- Undergraduate program in Applied Mathematics and Informatics, supervised by Associate Professor A.S. Konushin, Candidate of Sciences (PhD), is modeled after the leading programs in computer science offered at the Swiss Federal Institute of Technology of Lausanne, Switzerland, and Stanford University, USA. Thirteen to fifteen winners and awardees at the final stage of the All-Russian Olympiad of School Students are admitted to the program every year. The passing score in 2015 was 281 out of 300. The program focuses on training researchers, researchers in engineering and software developers.
- Master’s program in Data Sciences, supervised by professor S.O. Kuznetsov, Doctor of Sciences, is delivered in partnership with Kharkevich Institute, Skoltech, and Yandex School of Data Analysis. The program is devoted to Big Data processing and trains data-scientists who are in high demand on the global market today. Students in the program have the option of participating in academic mobility programs and spending a semester at Blaise Pascal University, Dresden University of Technology or Texas University in Brownsvill and receiving fully transferable credits.
An English-taught double-degree undergraduate program in computer sciences with the University of London is being developed and the first students will be enrolled in 2017.
Programs in software engineering sciences are delivered in partnership with the Institute for System Programming, Eindhoven University of Technology, IBM, Luхoft and Kaspersky Lab. Students are involved in research projects in compilation technologies, software verification, modelling and process mining in information systems.
- Undergraduate program in Software Engineering is aimed to train the best technical specialists, highly qualified software developers and software architects, quality assurance managers for software products and software development. The passing score in 2015 was 278 out of 300.
- Master’s program in System and Software Engineering is delivered in English and trains specialists in the industrial production of software. A separate program track is devoted to the design and development of mobile applications, from the fundamental principles of design to the practical aspects of the mobile product promotion. A new Master’s program in system programming in cooperation with the Institute for System Programming is scheduled to launch in 2017.
Educational programs through the HSE Moscow Institute of Electronics and Mathematics in applied mathematics and modelling are delivered in partnership with Dorodnicyn Computing Center, Trapeznikov Institute of Control Sciences, Space Research Institute, Keldysh Institute of Applied Mathematics. Students participate in research projects in mathematical and computer modelling.
- Undergraduate program in Applied Mathematics trains specialists who can tackle a wide range of tasks in the field of IT and contemporary engineering. Graduates have excellent career prospects working for multinational companies (Microsoft, Oracle, SAP, etc.).
- Master’s program in Mathematical Methods of Modelling and Computer Technologies, supervised by Professor M.V. Karasev, Doctor of Sciences, develops interdisciplinary competencies in mathematics and its applications in promising technological areas: supercomputer clusters, distributed computations, complex networks and statistical systems, diffusion waves and phase transitions. In 2015, Professor V.V. Stegailov, a senior lecturer in the program, received the Russian Presidential Award for Young Scientists in the Field of Science and Innovation.
In partnership with innovative companies and startups, Kharkevich Institute initiated two Master’s programs. Students enrolled in this program take part in research projects in machine learning, data mining and its applications.
- In 2015, the first students were enrolled in the Mathematical Optimization Methods and Stochastic Systems program, supervised by professor V.G. Spokoiny, Candidate of Sciences (PhD). The program is implemented in partnership with the Laboratory of Structural Data Analysis Methods in Predictive Modeling (PreMoLab) and Skoltech. Fourier University, Humboldt University and Airbus, Autodesk, and Huawei are among the program’s international partners. The program is designed to train researchers and analysts in the field of applied mathematics and mathematical modeling with an in-depth study of mathematical statistics, stochastic analysis and discrete mathematics, as well as specialists in methods of optimization. Students are involved in applied projects, including the traffic optimization project, implemented by the HSE Institute of Transport Economics and Transport Policy.
- Drawing on the success of this project, a Master’s program in Data Mining in Biology and Medicine will be launched in 2016 under the supervision of Professor M.S. Gelfand, Doctor of Sciences. Program partners include Belozersky Institute of Physico-Chemical Biology MSU, Vavilov Institute of General Genetics, Shemyakin - Ovchinnikov Institute of Bioorganic Chemistry, Moscow School of Bioinformatics, and Litech, Knomics, Atlas, Biomed Group, and iBinom companies. The program aims to train specialists in bioinformatics who will be able to develop computation methods and apply them to solving tasks in various areas of biology and medicine. The key advantage of this program is that it offers interdisciplinary education with in-depth knowledge of both mathematical tools and biological systems. Bioinformatics is extremely popular among undergraduate students at Russian universities; however, only 5 programs are currently being delivered throughout the whole country.
Key Research Projects and Their Development
The Faculty of Mathematics brought together a unique research team of leading mathematicians from all over the world. Their research projects are closely linked with cross disciplinary studies, which is the essential in modern mathematics. For example, 13 out of 21 plenary speakers invited to the International Congress of Mathematicians (Seoul, 2014) work in geometry, representation theory, dynamical systems, mathematical physics and number theory. Russia was represented only by four section speakers, and three of them are involved in Stategic Academic Unit’s research projects.
The Faculty of Computer Science was created with strong involvement from Yandex, and it is an example of full-scale collaboration between a university and a company, which is rare for Russia. Since 2015, a research team from the Laboratory of Methods for Big Data Analysis has participated in the LHCb experiment (one of the four experiments conducted at the Large Hadron Collider). Personnel from academic institutes and developers from the leading IT companies are engaged in teaching at the faculty.
Established in 1962, MIEM (Moscow Institute of Electronics and Mathematics) merged with HSE in 2012. Several MIEM research schools in various fields of applied mathematics, IT and engineering have become legendary. Some of the most prominent scholars work at MIEM, including academician V.P. Maslov, one of the leading experts in mathematical physics, and A.S. Holevo, an expert in quantum informatics and the winner of the 2016 Claude E. Shannon Award, alongside other outstanding experts.
The integration of these three university divisions within the framework of the unified Strategic Academic Unit will produce a substantial synergistic effect.
Key research projects:
1. Algebraic Geometry, Representation Theory and Mathematical Physics.
Project heads: Alexander Kuznetsov, Head of the HSE International Laboratory of Algebraic Geometry and its Applications, Leading Researcher at the Steklov Mathematical Institute, winner of the European Mathematical Society Prize 2008 and Russian Presidential Award for Young Scholars in the Field of Science and Innovation (2009) and Boris Feigin, head of the International Laboratory of Representation Theory and Mathematical Physics, professor at the HSE Faculty of Mathematics.
This project is dedicated to the development of Russian mathematics and groundbreaking research projects in fields that have already proved to be the bellwethers of the Moscow mathematical school as well as globally: algebraic geometry, differential geometry, complex geometry, representation theory, mathematical physics, number theory and dynamical systems.
The International Laboratory of Algebraic Geometry and its Applications, established in 2010 under the supervision of F.A. Bogomolov, professor at the Courant Institute of Mathematical Sciences (New York, USA), and International Laboratory of Representation Theory and Mathematical Physics, established in 2014 under the supervision of A.Y.Okunkov, Fields Medal Winner and professor at the Columbia University (New York, USA), are the key structural units in this project.
The project aims to achieve a number of specific targets, including the study of the interrelation between categorical joins and homological projective duality with application to building new examples of homologically projectively dual manifolds and creating new interrelations between derived categories; the study of minimal compactifications of basic affine varieties and building new examples of compactifications of affine varieties with application to higher dimensional Fano varieties, etc. The project is implemented in partnership with the Steklov Mathematical Institute.
2. Mathematical Methods in Theoretical Computer Science.
Project heads: Lev Beklemishev, Leading Research Fellow at the Steklov Mathematical Institute, Yandex professor at the HSE Faculty of Mathematics, Associate Member of the Russian Academy of Sciences (2006) and Nikolay Vereshchagin, professor at the HSE Faculty of Computer Science, member of the Academia Europaea: Informatics (2014).
Project fosters research in the field of theoretical computer science and related areas of mathematical logic: algorithmic information theory and algorithmic randomness, algorithmic statistics, provability logic and its application to arithmetic theories analysis, logical verification of communications protocol, logic means of representation and processing of data and knowledge.
International Laboratory for Intelligent Systems and Structural Analysis (leading research fellow - Andre Scedrov, Professor of Mathematics at the University of Pennsylvania) and International Laboratory of Theoretical Computer Science (leading international research fellow - Vladimir Gurvich, professor at Rutgers University, USA) are involved in project activities.
The principal subject of research in the algorithmic information theory is the size of the most concise description of finite objects. This theory will soon be extrapolated to algorithms with limitations on computetional resources (time and memory).
Another current objective is the study of provability logics and their application to the analysis of the first and the second order arithmetic theories. The project also includes the development and systematization of positive provability logics, specifically positive modal logic applications to the database theory and ontology languages.
3. Machine Learning and Data Mining with Applications in Information Technology, High Energy Physics, Biology, Medicine and Neuroscience.
Project heads: Sergei Kuznetsov, Head of the School of Data Analysis and Artificial Intelligence under the Faculty of Computer Science and Andrey Ustyuzhanin, Head of the HSE Laboratory of Methods for Big Data Analysis, supervisor of joint projects with Yandex company and CERN.
This project aims to develop data analysis methods with practical applications, including information retrieval, computer vision, biological, chemical and medical informatics, recommendation systems and computational linguistics.
The Bayesian methods team headed by Dmitry Vetrov works on integrating modern instruments of probabilistic modelling into learning algorithms of deep neural networks. A specific example of the projected application of the team’s activities is the compactification of neural network layers for use in mobile resources. One other promising area is the application of machine learning methods to high energy physics. HSE 2014-2015 research projects analyzing the results of experiments conducted at the Large Hadron Collider showed that a 40-60% increase in efficiency at various stages of data processing is quite possible. Specific tasks of the project include designing a cell phone-based system for data processing to be used for observing ultra-high energy space particles (A.E. Ustyuzhanin, D.A. Derkach). This technology could help to save the funds allocated for construction of costly observatories. Both project tracks are implemented in partnership with Skoltech and Yandex.
New projects dedicated to life sciences, the development of new methods in bioinformatics (M.S. Gelfand), mathematical neurobiology (A.E. Osadchy, B.S. Gutkin), medical informatics (S.O. Kuznetsov, O.S. Pyanykh), neurotechnologies (A.E. Osadchy, M. Feura) and cognitive technologies (T.Savada, I.S. Utochkin) are scheduled to be launched. HSE’s partners in these projects will include the Kharkevich Institute, Moscow Bioinformatic School and HSE Center for Cognition & Decision Making.
4. Process Mining: Modelling and Analysis of Information Systems Based on Their Real Behavior.
Project heads: Wil van der Aalst, full professor of Information Systems at the Eindhoven University of Technology (Netherlands), HSE Distinguished Professor, member of the Academy of Europe: Informatics and Irina Lomazova, Head of the HSE Laboratory of Process-Aware Information Systems.
This project aims to develop new approaches to increasing the efficiency, reliability and safety of modern information systems, based on the event log records that reflect real behavior of systems and their users. This project deals with Process Mining, which is a new and rapidly growing area of knowledge.
The HSE Laboratory of Process-Aware Information Systems was initiated by Professor Wil van der Aalst, the creator of process mining. HSE is a current member of the IEEE SIC Task Force on Process Mining, an international collaboration group that is comprised of leading academic and industrial centers. The examples of process mining practical applications include business process management systems (BPM), workflow management systems (WFM), enterprise resource planning systems (ERP) and case handling systems. The project’s goal is to develop new methods to analyze and design such systems. In process mining, comprehensive software products are created based on the LEGO principle – when a new method is introduced, a new plug-in is created and then incorporated into the complex. A module to adapt the existing model to real business processes, when there is no exact match between the model and process parameters, is being developed.
5. Mathematical and Computer Modelling.
Project heads: Mikhail Karasev, Head of the HSE Mathematical Methods in Natural Science Laboratory and Lev Shchur, Head of Information and Communication Facilities and Systems Joint Department with RAS Computing Center named after A.A. Dorodnitsyn.
This project deals with current issues in two interrelated areas: developing new mathematical methods for multi-scale modelling technologies and technical systems management at the macro level.
HSE partners in this project include the National University of Science and Technology MISiS, Irkutsk National Research Technical University, Space Research Institute of the Russian Academy of Sciences, Central Research Institute for Machine-building TSNIIMASH, Research and Manufacturing Association named after Lavochkin.
The integrated approach allows to significantly expand the range of project tasks - from atomic scale materials design, quantum informatics and bioinformatics to macro-level modelling and management of technical systems and processes. The project is dedicated to optimizing design concepts (including aerospace technology) for spaceflight dynamics, space missions trajectory plans, biomechanical systems modelling and artificial implants design for bone tissue.