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Article
Efficient indexing of peptides for database search using Tide

Acquaye F. L., Kertesz-Farkas A., Stafford Noble W.

Journal of Proteome Research. 2023. Vol. 22. No. 2. P. 577-584.

Article
Mint: MDL-based approach for Mining INTeresting Numerical Pattern Sets

Makhalova T., Kuznetsov S., Napoli A.

Data Mining and Knowledge Discovery. 2022. P. 108-145.

Book chapter
Modeling Generalization in Domain Taxonomies Using a Maximum Likelihood Criterion

Zhirayr Hayrapetyan, Nascimento S., Trevor F. et al.

In bk.: Information Systems and Technologies: WorldCIST 2022, Volume 2. Iss. 469. Springer, 2022. P. 141-147.

Book chapter
Ontology-Controlled Automated Cumulative Scaffolding for Personalized Adaptive Learning

Dudyrev F., Neznanov A., Anisimova K.

In bk.: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium -23rd International Conference, AIED 2022, Durham, UK, July 27–31, 2022, Proceedings, Part II. Springer, 2022. P. 436-439.

Book chapter
Triclustering in Big Data Setting

Egurnov D., Точилкин Д. С., Ignatov D. I.

In bk.: Complex Data Analytics with Formal Concept Analysis. Springer, 2022. P. 239-258.

Article
Triclusters of Close Values for the Analysis of 3D Data

Egurnov D., Ignatov D. I.

Automation and Remote Control. 2022. Vol. 83. No. 6. P. 894-902.

Article
Deep Convolutional Neural Networks Help Scoring Tandem Mass Spectrometry Data in Database-Searching Approaches

Kudriavtseva P., Kashkinov M., Kertész-Farkas A.

Journal of Proteome Research. 2021. Vol. 20. No. 10. P. 4708-4717.

Article
Language models for some extensions of the Lambek calculus

Kanovich M., Kuznetsov S., Scedrov A.

Information and Computation. 2022. Vol. 287.

Basic Department ‘Mathematical Methods of System Analysis’ at the Institute for System Analysis of the Russian Academy of Sciences

The synergy of educational and research processes is essential for the education of future qualified specialists and researchers. The practice, implemented from the first higher education stages, has become  traditional for the Moscow School of System Analysis. Maintaining and developing this tradition is an important objective  for both the HSE, and the ISA RAS.  Establishing the Basic Department ‘Mathematical Methods of System Analysis’, at the ISA RAS will contribute to this objective.

The Institute for System Analysis (ISA) is a part of the RAS Department for Nanotechnologies and Information Technologies. The institute not only successfully solves basic and applied scientific problems of system analysis and information technologies, but also coordinates major scientific projects, and educates young scientists.

Scientific staff of the ISA unites competent and highly skilled specialists, including four RAS acting members, three RAS corresponding members, 50 Doctors and more than 100 Candidates of Sciences in Physics, Mathematics, Technology, Economics, Philosophy, Sociology, and Geography.

Among the major results of the ISA’s research work are  the theory of control for uncertain nonlinear systems (Academician S.Emelianov); the macrosystem theory (Y.Popkov, RAS Corresponding Member); system modeling methods (Academician V.Gelovani); artificial intelligence methods for information behavior, search, and analysis modeling (G.Osipov, PhD in Physics and Mathematics); methods of symbol and audio object recognition, and database control (V.Arlazarov, RAS Corresponding Member); organizing methods of the distributed computing environment (A. Afanasiev, PhD in Physics and Mathematics); information security methods (D.Chereshkin, PhD in Technical Sciences); mathematical support and technologies for rapid construction of information systems, and automation of document processing; methodology for construction of bio-ecosystem simulation modeling, biomedical monitoring automated systems, and regional environment forecasting (S.Pegov, PhD in Technical Sciences; V.Krutko, PhD in Technical Sciences); efficiency theory and methods of investment projects evaluation (V.Livshits, PhD in Economics); methods of system diagnostics and regulation of spatially distributed organizational structures (V.Leksin, PhD in Economics; A.Shvetsov, PhD in Economics); theory basics and mechanisms of cross-sectoral social partnership (V. Jakimets, PhD in Social Sciences). The Institute’s applied research projects  also enjoy a prominent place.

The establishment of the ISA Department at the HSE  is another step towards partnership between the RAS Institute for System Analysis and the HSE. The Department will make the Faculty of Business Informatics and the School of Applied Mathematics and Information Science more attractive to potential students and postgraduate students, both Russian and international, who want to do applied research in system analysis, and applications.

The synergy of educational and research processes is essential for the education of future qualified specialists and researchers. The practice, implemented from the first higher education stages, has become  traditional for the Moscow School of System Analysis. Maintaining and developing this tradition is an important objective  for both the HSE, and the ISA RAS.  Establishing the Basic Department ‘Mathematical Methods of System Analysis’, at the ISA RAS will contribute to this objective.

Y. Popkov, RAS Corresponding Member, is appointed Head of the Department. The lecturing staff include research fellows of the ISA, such as V.Arlazarov, RAS Corresponding Member; G.Osipov, Professor, PhD in Physics and Mathematics; V.Krivonozhko, Professor,PhD in Physics and Mathematics; N.Magnitsky, Professor, PhD in Physics and Mathematics; E.Orlova, Professor, PhD in Economics; B.Darhovsky, Professor, PhD in Physics and Mathematics; A.Bakushinsky, Professor, PhD in Physics and Mathematics.

Courses:

  • Macro-system theory (Y.Popkov)
  • Methods of big data system analysis and projection (V.Arlazarov)
  • Artificial intelligence models and methods (G.Osipov)
  • Techniques of corporation system optimization (V.Krivonozhko)
  • Chaotic dynamics (N.Magnitsky)
  • Information technologies of investment projects evaluation (E.Orlova)
  • Methods of composite hypothesis testing (B. Darhovsky)
  • Interactive methods of wrong problem solving, and optimization (A.Bakushinsky)