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Laboratory of Mathematical Cybernetics and Computing Technologies

Head of the laboratory, Academician of NAS RK, Dr.Sc. (Phys.-Math.),

Prof. M.N. Kalimoldayev

Objectives of the Laboratory of Mathematical Cybernetics and Computing Technologies.

The Laboratory of Mathematical Cybernetics and Computing Technologies (hereinafter referred to as the Laboratory) focuses on fundamental and applied research in the field of mathematical modeling of complex control systems, information processes, and computing methods.

  1. Development of theoretical foundations of mathematical cybernetics: Creation and analysis of mathematical models for describing dynamic systems, including stochastic processes, nonlinear equations, and optimization algorithms, with the aim of improving control efficiency in cybernetic systems.
  2. Innovations in computing technologies: Development of high-performance algorithms and software tools for parallel computing, machine learning, and big data processing, enabling real-time problem solving in distributed systems.
  3. Integration of cybernetics and computational methods in interdisciplinary fields: Application of mathematical approaches of cybernetics for modeling biological, economic, and technical systems, including artificial intelligence, robotics, and quantum computing, with an emphasis on sustainability and adaptability.
  4. Training of scientific personnel and knowledge transfer: Building the competencies of young professionals through educational programs, seminars, and publications, as well as transferring research results to industry and education to stimulate technological progress.

Objectives of the Laboratory of Mathematical Cybernetics and Computing Technologies

To achieve these goals, the Laboratory addresses the following key objectives, structured by area of activity:

1. Theoretical research:

Development of mathematical models of cybernetic systems based on the theory of automata, differential equations, and graph structures for stability and controllability analysis.

Study of stochastic and deterministic optimization algorithms, including gradient methods, genetic algorithms, and neural networks, taking into account computational complexity.

2. Applied research:

Development of software for simulating cybernetic processes, including tools for parallel and real-time data processing.

Modeling and optimization of computing networks, including cloud and distributed systems, with a focus on reducing energy consumption and improving fault tolerance.

3. Experimental and computational work:

Conducting numerical experiments using high-performance computing clusters to verify mathematical models for forecasting and control tasks in electric power systems.

Analyzing big data using machine learning methods to identify patterns in cybernetic systems, including clustering, classification, and regression.

4. Collaboration and implementation:

Organization of interdisciplinary projects with partners from academia, industry, and government agencies to test developments in real-world scenarios.

Publishing results in leading scientific journals and participating in international conferences to exchange knowledge.

The Laboratory’s activities are based on the principles of scientific rigor, ethics, and innovation, taking into account contemporary challenges in the field of digital transformation and sustainable development.

International cooperation

  1. Al-Farabi Kazakh National University, Almaty, Kazakhstan
  2. Uşak University, Uşak, Turkey
  3. Georgia State University, Atlanta, Georgia, USA
  4. Lublin University of Technology, Lublin, Poland
  5. Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch of the Russian Academy of Sciences (ICMMG SB RAS), Novosibirsk, Russia
  6. 6. Moscow State University of Geodesy and Cartography (MGU), Moscow, Russia
  7. Federal Research Center for Information and Computing Technologies (FRC ICT SB RAS), Novosibirsk, Russia

Articles

  1. 1. Gulnar Zholdangarova, Maksat Kalimoldaev, Gulzat Ziyatbekova, Mukaddas Arshidinova Development of algorithms and software for researching the stability of complex energy systems // Carpathian Mathematical Publications, ISSN 2075-9827, E-ISSN 2313-0210. (Q1) https://doi.org/10.15330/cmp.17.2.376-385
  1. V. B. Barakhnin, S. V. Maltseva, M. N. Kalimoldaev, K. O. Alekankin Modeling of electricity consumption in a socio-technical system using a flexible tariff accounting system // Computing Technologies, 30(3): 5-22 DOI:10.25743/ICT.2025.30.3.002

Defense of doctoral dissertation

  1. Thesis for the degree of Doctor of Philosophy (PhD) by Bapyshev Akylbek Mirzabekovich on the topic: “Development of a method for calculating the guaranteed fuel reserve for controlling the descent of spent stages of carrier rockets” in the specialty “8D07111 – Space Technology and Technologies”.
  2. Doctoral dissertation by Mekebaev Nurbopa Otanovich on the topic  “Identification and correction of errors in machine learning algorithms” in the field of “6D060200 – Informatics.”

Intellectual property certificates

  • AKHMETZHANOV MAKSAT AKANOVICH, Kydyraly Abylai Sabyrzhanuly Mobile application for energy consumption management on the Android platform (PowerMonitor) 10.06.2025 No. 59505
  • AKHMETZHANOV MAKSAT AKANOVICH, Kalimoldaev Maksat Nuradilovich, Toleugazy Sayat, Nurtasuly, Nurpeisova Dina Nurtashkyzy, Arshidinova Mukaddas Turganovna Certificate of entry of information into the state register of rights to objects protected by copyright dated 3.11.2024 EGKZ – Energy Guard KZ No. 51577
  • ZIATBEKOVA GULZAT ZIATBEKKYZY, Kalimoldaev Maksat Nuradilovich, Akhmetzhanov Maksat Akanovich, Arshidinova Mukaddas Turganovna, Zholdangarova Gulnar Igibaevna Certificate of entry of information into the state register of rights to objects protected by copyright dated 18.12.2024 DEVELOPMENT OF A MICROPROCESSOR DATA TRANSMISSION SYSTEM FOR MONITORING THE LOAD OF ELECTRICAL POWER SYSTEMS No. 42841
  • RAIMZHANOV DAVRON RAMATZHANOVICH, Akhmetzhanov Maksat Akanovich, Kadyrova Zarina Vinerovna Author’s object: Program dedicated to EEM, ITG (IoTGrad), 09.12.2024  No. 52522