Askhat Diveev | Computational Methods | Excellence in Research

Posted on by sciencefather

Prof. Askhat Diveev | Computational Methods | Excellence in Research 

Prof. Askhat Diveev, Federal research center Computer Science and Control of RAS,  Russia

Prof. Askhat Diveev is a renowned computational scientist and expert in control systems and machine learning methods. Based at the Federal Research Center for Computer Science and Control of RAS, he has authored over 400 scientific publications and mentored multiple scholars in their academic journeys. His innovative contributions to numerical methods, genetic programming, and traffic flow modeling have earned him international recognition. His dedication to advancing computational sciences continues to inspire the global research community.

PROFILE

Orcid  Profile

Educational Detail

Prof. Askhat Diveev has a distinguished academic foundation in computational science and numerical methods. He has mentored numerous scholars, successfully guiding eight candidates of sciences and one doctor of sciences.

Professional Experience

Prof. Diveev is a leading researcher at the Federal Research Center for Computer Science and Control, Russian Academy of Sciences (RAS). With over 400 published scientific papers and 148 indexed in Scopus, he holds a Hirsch index of 14 in Scopus and 9 in WoS. His expertise lies in the development of advanced numerical methods and machine learning techniques, which have been applied to various fields, including traffic flow modeling and control systems. Additionally, he has authored a book (ISBN: 978-3-030-83213-1) and holds significant contributions to applied mathematics and computer science.

Research Interests

Prof. Diveev’s research focuses on numerical methods for control problems, symbolic regression, genetic programming, and mathematical modeling. His groundbreaking work includes:

Developing a numerical method for general control synthesis using symbolic regression in machine learning.

Innovating the principle of small variations of the basis solution for mathematical expressions in non-numerical spaces.

Advancing variation genetic programming methodologies, including Cartesian and binary genetic programming.

Creating a recurrent, finite-difference mathematical model for urban traffic light control systems.

Top Notable Publications

1. Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (November)

DOI: 10.3390/math12223595

Citations: Citation details currently unavailable; updates depend on indexing databases like Scopus or WoS.

2. Advanced Model with a Trajectory Tracking Stabilisation System and Feasible Solution of the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2024 (October)

DOI: 10.3390/math12203193

Citations: Citation details currently unavailable.

3. A Stabilisation System Synthesis for Motion along a Preset Trajectory and Its Solution by Symbolic Regression

Authors: A. Diveev et al.

Year: 2024 (February)

DOI: 10.3390/math12050706

Citations: Citation details currently unavailable.

4. Adaptive Synthesized Control for Solving the Optimal Control Problem

Authors: A. Diveev et al.

Year: 2023 (September)

DOI: 10.3390/math11194035

Citations: Citation details currently unavailable.

5. Universal Stabilisation System for Control Object Motion along the Optimal Trajectory

Authors: A. Diveev et al.

Year: 2023 (August)

DOI: 10.3390/math11163556

Citations: Citation details currently unavailable.

6. Reinforcement Learning for Solving Control Problems in Robotics

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033029

Citations: Citation details currently unavailable.

7. Stabilization of Movement along an Optimal Trajectory and Its Solution

Authors: A. Diveev et al.

Year: 2023 (June)

DOI: 10.3390/engproc2023033012

Citations: Citation details currently unavailable.

8. Additional Requirement in the Formulation of the Optimal Control Problem for Applied Technical Systems

Authors: A. Diveev et al.

Year: 2023 (May)

DOI: 10.3390/engproc2023033007

Citations: Citation details currently unavailable.

Conclusion 

Based on his extensive academic and professional background, impactful research innovations, high citation metrics, and substantial contributions to theoretical and applied sciences, Prof. Askhat Diveev is highly suitable for the Excellence in Research recognition. His work exemplifies the qualities of a leader in the research community, combining innovation, mentorship, and practical applications.