Mr. Muhammad Abbas | Mathematics | Best Researcher Award

Published on by Robotics and Automation

Mr. Muhammad Abbas | Mathematics | Best Researcher Award

University of Peshawar | Pakistan

Mr. Muhammad Abbas is an MPhil scholar in the Department of mathematics at the University of Peshawar, Pakistan, specializing in dynamic systems and neural network models. His academic jouney reflects a deep commitment to understanding complex systems through mathematical modeling and analytical methods. His primary research interests include dynamic systems, neural network models, fixed point theory, time scale theory, Mathematics and control theory. Muhammad abbas has contributed three research papers published in reputed journals indexed in scopus and other international databases, earning a total of 3 citations and achieving an h-index of 1. His recent study makes a pioneering contribution by examining synchronization and stability issues in a network of spiking neural networks with time delays over time scales. this innovative work introduces new control strategies-feedback and output control protocols-to achieve ulam-hyers-rassias stability and exponential synchronization. Through his growing research portfolio, Muhammad Abbas aims to advance the mathematical foundations of neural systems and control theory while bridging the gap between theoretical research and real-world computational models. With a focus on quality research and academic excellence, he continues to explore emerging intersections between mathematics and intelligent systems, contributing to the broader development of computational and applied mathematical sciences.

Profile: Scopus

Featured Publication

Abbas, M. (2025). Exponential synchronization and Ulam-Hyers-Rassias stability for n spiking neural networks with time delays via different controller matrix over a time scale. Ain Shams Engineering Journal.

Dr. A. Sreenivasulu | Dynamic system on time scales | Best Researcher Award

Published on by Robotics and Automation

Dr. A. Sreenivasulu | Dynamic System on Time Scales | Best Researcher Award

Koneru Lakshmaiah Education Foundation | India

Dr. a. sreenivasulu is an assistant professor of mathematics at Koneru lakshmaiah education foundation, India, with a specialization in dynamical systems on time scales. he earned his b.sc from Sri Venkateshwara University, followed by m.sc in mathematics from osmania university, and a ph.d. in applied mathematics, where his thesis explored first-order matrix sylvester and volterra integro-dynamic systems on time scales. over his more than ten years of teaching and research experience, he has taught a broad suite of courses- engineering mathematics, numerical analysis, operations research, partial differential equations, probability & statistics, etc. Across several institutions. his research output includes 12 published documents dealing with stability, controllability, observability, periodic and impulsive behaviour of matrix sylvester and volterra integro-dynamical systems. according to google scholar, his works have been cited 18 times, giving him an h-index of 3, with notable contributions such as “stability criteria for nonlinear volterra integro-dynamic matrix sylvester systems on measure chains” cited up to eight times across sources, and “exponential stability of volterra integro-dynamic sylvester matrix system on time scales” already attracting citations. his scholarly identifiers include orcid, scopus author id, wos id, and vidwan id, and his ongoing work continues to enhance the scope of applied mathematics in interdisciplinary domains.

Profiles: Scopus | Orcid

Featured Publications

"Controllability for Volterra Integro-Dynamic Sylvester Matrix Systems with Impulse on Time Scales"

"Exponential Stability of Volterra Integro-Dynamic Sylvester Matrix System on Time Scales"

"Periodic and Pseudo Periodic Solutions for Matrix Sylvester Dynamic System on Measure Chains"

"Unstationary Viscoelastic MHD Flow of Walters-B Liquid through a Vertical Porous Plate with Chemical Reactions"

"Periodic Solution for Almost Linear Volterra Integro-Dynamic Matrix Sylvester System on Measure Chains"