Jalil Manafian | Applied Mathematics | Best Researcher Award

Askhat Diveev | Computational Methods | Excellence in Research

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.

 

 

 

 

 

 

 

 

 

 

Abdisalam Hassan Muse | Computational Methods | Best Researcher Award

Assoc Prof Dr. Abdisalam Hassan Muse | Computational Methods | Best Researcher Award 

Assoc Prof Dr. Abdisalam Hassan Muse, Amoud University, Somalia

Assoc. Prof. Dr. Abdisalam Hassan Muse is an accomplished educator and researcher, with a Ph.D. in Statistics from PAUSTI-JKUAT, Kenya. He has over 13 years of experience teaching mathematics, statistics, and data science at both secondary and university levels. Dr. Muse has a strong research focus on Bayesian statistics, econometrics, and data science, with expertise in statistical modeling, machine learning, and time series analysis. His academic work is complemented by active participation in international workshops and trainings in advanced statistical methods.

Orcid Profile

Educational Details

Assoc. Prof. Dr. Abdisalam Hassan Muse earned his Ph.D. in Statistics from the Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), hosted at Jomo Kenyatta University of Agriculture and Technology (JKUAT), Nairobi, Kenya (May 2019 – Oct 2022). He also holds two Master’s degrees: an MSc in Climate Change and Environmental Sustainability from Amoud University, Borama, Somalia (September 2018 – Incomplete), and an MSc in Mathematics and Statistics from the same institution (September 2015 – July 2017). His diverse academic foundation also includes a BA in Islamic Studies from Beder International University, Borama, Somalia (September 2013 – July 2016), a BSc in Mathematics and Physics from Amoud University (September 2010 – July 2012), and Diplomas in Islamic Studies (2008–2010) and Education for Mathematics and Physics (2005–2007) from Amoud University and Zaylac Institute of Islamic Studies, respectively. He completed his secondary education at Sheikh Ali Jawhar Secondary School in Borama, Somaliland, earning the Somaliland Certificate of Secondary Education (September 2001 – July 2005).

Professional Experience

Dr. Abdisalam Hassan Muse has over 13 years of experience in education, including two years of postgraduate teaching and supervision and six years of undergraduate university teaching. His teaching expertise spans mathematics, statistics, data science, and the application of technology in statistical experiments. He also has 11 years of secondary teaching experience. Throughout his career, he has demonstrated a strong ability to communicate complex concepts, both in academic and classroom settings. Dr. Muse has actively participated in several international workshops and training programs, focusing on Bayesian statistics, data science, official statistics, disease modeling, and statistical software like R and Python. Additionally, he has experience in research and training related to fragile environments and post-distribution monitoring for aid programs.

Research Interest

Dr. Muse’s research is focused on a variety of statistical fields, including Bayesian statistics, econometrics, survival analysis, official statistics, and demography. His expertise extends to data science, statistical modeling, machine learning, mathematical statistics, and stochastic processes. He has a passion for applying advanced statistical techniques to real-world problems, with a keen interest in environmental statistics, computational statistics, probability distributions, regression modeling, and time series analysis. His skills also encompass areas like Ito calculus, education statistics, and population analysis.

Top Notable Publications

Prevalence and determinants of home delivery among pregnant women in Somaliland: Insights from SLDHS 2020 data
Atención Primaria
2025-02 | Journal Article
DOI: 10.1016/j.aprim.2024.103082
ISSN: 0212-6567
Source: Abdisalam Hassan Muse

Cardiovascular disease prevalence and associated factors in a low-resource setting: A multilevel analysis from Somalia’s first demographic health survey
Current Problems in Cardiology
2024-12 | Journal Article
DOI: 10.1016/j.cpcardiol.2024.102861
Source: Crossref

Prevalence and determinants of hypertension among adults in Somalia using Somalia demographic health survey data, SDHS 2020
Current Problems in Cardiology
2024-11 | Journal Article
DOI: 10.1016/j.cpcardiol.2024.102783
ISSN: 0146-2806
Source: Abdisalam Hassan Muse

Analyzing Unimproved Drinking Water Sources and Their Determinants Using Supervised Machine Learning: Evidence from the Somaliland Demographic Health Survey 2020
Water
2024-10 | Journal Article
DOI: 10.3390/w16202986
Source: Multidisciplinary Digital Publishing Institute

Conclusion

Assoc. Prof. Dr. Abdisalam Hassan Muse is a highly qualified candidate for the Best Researcher Award. His strong educational background, extensive professional experience, and commitment to impactful research make him a standout in the field of statistics and data science. Dr. Muse’s innovative approach, coupled with his dedication to community engagement, positions him as a leading figure in advancing computational methodologies for the betterment of society.