Research activities

The University actively participates in competitions for scientific and scientific and technical activities, as a result of which projects of grant financing of the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan are implemented with a total amount of over 500 million tenge for 2021-2023..

Projects:

1) Topic name: IT assessment of scientific activities of universities, research institutes and their departments

Scientific adviser: Biloshchytskyi A.A.

Name of the project: RK MSC, 2020-2022 years (27 months)

Result, amount: 60.141 mln.tg

Annotaion:

In order to modernize the scientific, technical and innovative development of the Republic of Kazakhstan, effective tools for assessing the results of research activities of scientists, universities and research institutes should be created. This makes it possible to check the compliance of the research process with the goals that were indicated at the stage of their planning and, if necessary, adjust the course of these studies. Also, the estimates obtained are an effective tool for planning funding for these studies.

For the formation of teams for joint research, a typical approach is to select partners from among scientists with the appropriate qualifications and experience in implementing similar projects. Establish effective collaboration within scientific communities and scientifically based team building that are able to successfully implement projects that are especially important for project-oriented organizations, research institutes and universities.

2) Topic name: Noncommutative symmetric spaces and related problems

Scientific adviser: Raikhan M.

Name of the project: RK MSC, 36 months 2021-2023

Result, amount: 60.141 mln.tg

Annotaion:

As a result of research on the project, a connection will be obtained between the generalized singular values of the matrix of measurable operators and the generalized singular numbers of its elements and its applications, Young-type inequalities will be proved for the generalized singular number of measurable operators associated with the semifinite von Neumann algebra. We will obtain properties of commutative and non-commutative weak Orlicz spaces, non-commutative versions of weak Orlicz spaces associated with states and weights. An atomic decomposition for non-commutative martingale symmetric spaces and its applications will be obtained. The expected results of the project will significantly advance the qualitative theory of non-commutative Orlicz space and the theory of martingales.

3) Topic name: Hybrid modeling of the energy system for development of renewable energy roadmap for Kazakhstan with high spatial, temporal and technical disaggregation

Scientific adviser: Zhakiyev N.

Name of the project: RK MSC, 36 months 2021-2023

Result, amount: 46.36 mln.tg

Annotaion:

As a result of the project, an integrated energy system modeling tool will be created to develop a roadmap for the development of renewable energy in Kazakhstan using advanced world modeling solutions with high spatial, technical and temporal disaggregation to account for the variability of renewable energy sources.

4) Topic name: Application of modeling methods and machine learning for optimal planning of the load of the generating equipment of Pavlodar CHP

Scientific adviser: Zhakiyev N.

Name of the project: RK MSC, 12 months 2021

Result, amount: 8 mln.tg

Annotaion:

Investigation of the potential for increasing the energy efficiency of CHP plants, reducing greenhouse gas emissions and the use of machine learning methods for optimal planning of the composition of the generating equipment of the CHP plant in Pavlodar, Kazakhstan.  This study is important for the applied testing of big data processing methods using machine learning methods coming from an industrial facility that generates electricity, heat, and industrial steam. Pavlodar CHPP is special in that it has two different consumers in the person of the aluminum plant and the population. The complexity in the variability of the consumption profile requires the use of modern methods of predictive planning of the composition of generating equipment for a day or a week. The long service life of the units, the hours worked requires constant adjustment of the repair plan for the year ahead. It is necessary to take into account the dynamic demand curve for heat and electricity using forecasting methods depending on the weather, the variability of heat and electricity consumption, which changes by probabilistic laws based on historical data of the consumption profile.

5) Topic name: Development of intelligent information and telecommunication systems for urban infrastructure: transport, ecology, energy and data analytics in the Smart City concept

Scientific adviser: Akhmed-Zaki D.Z.

Name of the project: RK MSC, 36 months 2021-2023

Result, amount: 390 mln.tg

Annotaion:

The main idea of the project is to develop a complex of intelligent information and communication systems for the development of urban infrastructure, which involves improving the quality of life of citizens by improving the transport infrastructure, developing the environmental situation, efficient use of energy resources and introducing the principles of predictive data analytics for making management decisions in the Smart concept. City.

To motivate young scientists, the university annually allocates intra-university grants for the implementation of scientific project.

 

1)         Sarsenova Z. – Development of a monitoring and analysis system for air pollution in the city of Nur-Sultan using the Data-driven approach

2)         Kassymkhanov S. – Application of modeling and machine learning methods to analyze heat energy consumption by zones of the city of Nur-Sultan

3)         Kharmyssov C. – Construction of a patient-specific eye model for glaucoma research

4)         Alimzhanov E. – Using the Nvidia Omniverse Platform to Create a Virtual University

AITU faculty actively publishes scientific works in publications indexed in Scopus and Web of Science with quartile Q1-Q2.

https://www.scopus.com/affil/profile.uri?afid=60204069