Assistant Professor at Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan, Pakistan
Dr. Muhammad Saqib is a distinguished mathematician specializing in numerical analysis, computational mathematics, and the numerical solution of partial differential equations (PDEs). He is currently an Assistant Professor at the Institute of Mathematics, Khwaja Fareed University of Engineering and Information Technology (KFUEIT), Pakistan. With a strong academic and research background, Dr. Saqib has contributed significantly to mathematical modeling, finite difference and finite volume methods, and computational approaches to solving complex mathematical problems. He has held key academic positions at NUML University, Air University Islamabad, and King Abdul Aziz University, Saudi Arabia.
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Education Background
- Ph.D. in Numerical Analysis (2017) – King Abdul Aziz University, Saudi Arabia
- M.S. in Mathematics (Mathematical Modeling & Simulation) (2011) – Blekinge Institute of Technology, Sweden
- B.S. in Mathematics (2008) – International Islamic University, Islamabad, Pakistan
Dr. Saqib has extensive experience in academia and research. He has served as an Assistant Professor at KFUEIT, NUML University, and Air University Islamabad. Previously, he worked as a Research Associate at King Abdul Aziz University, where he contributed to advanced computational techniques for solving nonlinear PDEs. At KFUEIT, he plays vital roles as BASR Coordinator, Secretary DGC, and Exam Coordinator. His research has been supported by grants from the Higher Education Commission (HEC) of Pakistan, focusing on novel numerical algorithms for complex mathematical systems.
Research Focus
- Numerical Analysis of PDEs
- Finite Difference and Finite Volume Methods
- Computational Mathematics and Bio-Mathematics
- Compact Finite Difference Schemes
Author Metrics:
Dr. Muhammad Saqib has established a strong academic presence through his research contributions, which are reflected in his author metrics. His publications are indexed in well-reputed journals such as IEEE Access, Physica Scripta, and Partial Differential Equations in Applied Mathematics. His Google Scholar profile showcases a growing number of citations, highlighting the impact of his research in numerical analysis and computational mathematics. As a researcher specializing in numerical methods for partial differential equations, finite difference schemes, and computational modeling, his work has gained recognition in the fields of applied mathematics, engineering, and bio-mathematics. The increasing citation count and visibility of his research demonstrate his influence in advancing mathematical techniques for real-world applications.
Awards and Honors:
Dr. Saqib has received notable academic and research accolades throughout his career. He was awarded the Doctoral Fellowship (2014–2017) by King Abdul Aziz University, Saudi Arabia, in recognition of his outstanding research potential during his Ph.D. studies. His work in numerical methods and computational solutions has been further supported by competitive research funding, including the Start-up Research Grant Program (SRGP) from the Higher Education Commission (HEC) of Pakistan in 2019–2020. This grant, amounting to PKR 361,000, funded his research on the nonlinear Burgers-Huxley system, emphasizing the development of efficient numerical techniques. These honors reflect his academic excellence, innovative research contributions, and commitment to advancing the field of numerical analysis and computational mathematics.
Publication Top Notes
1. Finite Volume Modeling of Neural Communication: Exploring Electrical Signaling in Biological Systems
- Authors: M. Saleem, M. Saqib, B.S. Alshammari, S. Hasnain, A. Ayesha
- Journal: Partial Differential Equations in Applied Mathematics
- Volume: 13
- Article ID: 101082
- Year: 2025
- Abstract: This paper employs finite volume methods to simulate neural communication, focusing on electrical signal propagation in biological systems. The study contributes to computational neuroscience by providing an efficient numerical approach to model and analyze neural activity.
2. Analyzing Stability and Dynamics of an Epidemic Model with Allee’s Effect and Mass Action Incidence Rates Incorporating Treatment Strategies
- Authors: M. Qurban, A. Khaliq, M. Saqib
- Journal: Physica Scripta
- Year: 2024
- Abstract: The research examines an epidemic model integrating Allee’s effect and mass action incidence rates. Stability analysis and numerical simulations provide insights into the effectiveness of treatment interventions in disease control.
3. Numerical Study of One-Dimensional Fisher’s KPP Equation with Finite Difference Schemes
- Authors: S. Hasnain, M. Saqib
- Journal: American Journal of Computational Mathematics
- Volume: 7 (1)
- Pages: 70
- Year: 2017
- Abstract: This study applies finite difference schemes to the Fisher-KPP equation, a fundamental reaction-diffusion model. It evaluates the stability, convergence, and efficiency of various numerical approaches in solving biological wave propagation problems.
4. Highly Efficient Computational Methods for Two-Dimensional Coupled Nonlinear Unsteady Convection-Diffusion Problems
- Authors: M. Saqib, S. Hasnain, D.S. Mashat
- Journal: IEEE Access
- Volume: 5
- Pages: 7139-7148
- Year: 2017
- Abstract: The paper presents high-accuracy computational methods for solving two-dimensional convection-diffusion problems, which frequently arise in fluid dynamics, heat transfer, and atmospheric modeling. The proposed methods enhance computational efficiency and stability.
5. Computational Solutions of Two-Dimensional Convection-Diffusion Equation Using Crank-Nicolson and Time-Efficient ADI Schemes
- Authors: M. Saqib, S. Hasnain, D.S. Mashat
- Journal: American Journal of Computational Mathematics
- Volume: 7 (3)
- Pages: 208
- Year: 2017
- Abstract: This research explores Crank-Nicolson and Alternating Direction Implicit (ADI) schemes for solving convection-diffusion equations. It highlights the efficiency and accuracy of these numerical techniques in computational fluid dynamics applications.
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