Department of Applied Mathematics and Artificial Intelligence

Systems of Artificial Intelligence, decision making, knowledge processing. Methods of data mining, machine learning, neural network and cognitive technologies.

Programming technology, databases.

Parallel and distributed systems, use of clusters, high performance and cloud computing.

WEB-programming and network technologies.

Means and methods of data protection.

Computer graphics, interface development.

Computer modeling, optimization methods, computer training tools.

Discrete mathematics, graph theory.

Integrated methods and models for representing and operating ill-defined information in intelligent real-time decision support systems (project No. 20-07-00498), 2020-2022. (head – professor Eremeev A.P.)

Modeling the reasoning of a cognitive agent based on non-classical logics, RFBR grant (project No. 20-57-00015-Bel_a), 2020-2021. (head – professor Fominykh I.B.)

Methods and algorithms for intelligent analysis of big data in decision support systems for digital economy problems, RFBR grant (project No. 18-29-03088-mk), 2018-2021. (head – professor Fominykh I.B.)

Models of parallel processes and dynamically reconfigurable systems for their efficient implementation, RFBR grant (project No. 18-01-00548-a), 2018-2020. (head – professor Kutepov V.P.)

Modeling plausible reasoning in intelligent systems based on precedents, fuzzy logic methods and a multi-agent approach, RFBR grant (project No. 18-01-00459-a), 2018-2020. (head – associate professor Varshavskii P.R.)

Methods and tools for knowledge discovery in intelligent decision support systems, RFBR grant (project No. 17-07-00442-a), 2017-2019. (head – professor Vagin V.N.)

Methods and software tools for designing intelligent decision support systems based on temporal models, RFBR grant (project No. 17-07-00553-a), 2017-2019. (head – professor Eremeev A.P.)

Development of methods and software for machine learning using argumentation theory and deep learning networks, grant of the President of the Russian Federation MK-2897.2017.9, 2017-2018. (head – associate professor Morosin O.L.)

The Department of Applied Mathematics and Artificial Intelligence provides training for professional programmers who are able to develop system and applied software, as well as conduct scientific work in various fields of computer science, including such a promising area as artificial intelligence and intelligent systems.

Graduates of the AM&AI department receive fundamental training in classical and constructive mathematics, computer science, mathematical logic, theory and programming systems, probability theory and mathematical statistics, organization of databases and knowledge, operations research and decision theory, graph theory, semantics of programming languages, methods of artificial Intelligence.

Participation in the work of scientific groups under the guidance of well-known scientists enables students and graduate students of the AM&AI department to reach the forefront of the most promising areas in the field of information technology and be in demand as specialists to solve modern problems of the digital economy.

The department is equipped with modern equipment and software. There are two educational laboratories (computer classes) equipped with workstations, united in a computer network based on multi-core processors with parallel information processing facilities. 

As software tools, software products developed by the team of authors are used:

– a complex for designing real-time decision support systems SIMPR-WINDOWS;

– base modules of the second version of the SIMPR-WINDOWS decision-making modeling system, extended by means of processing decision tables with extended input and fuzzy decision tables (Fuzzy Decider);

– a software tool for constructing case libraries and finding a Case-Based Reasoning (CBR);

– a system for modeling temporal reasoning based on a point model of time;

– a system for retrieving knowledge relevant to a problem situation (SCM) from the corporate memory;

– case-based data analysis software tool; 

Modular Case System Architecture

– a prototype of an intelligent decision support system (IDS) for the analysis and diagnosis of complex problematic situations on the example of vision pathologies, etc.

General scheme of the IDSS prototype for the analysis of problem situations

Bachelor

01.03.02, Applied Mathematics and Informatics,
profile: Mathematical and software support for computers and computer networks

Master

01.04.02, Applied Mathematics and Informatics,
profiles:

Mathematical and software support for computers and computer networks

Artificial Intelligence

PhD

2.3.5, Mathematical and software support for computing systems, complexes and computer networks

2.3.8, Informatics and information processes