Vice President at NUST, Pakistan
Summary:
Mr. Atif Rehman is a graduate in Computational Sciences and Engineering with a special focus on control systems, having earned his Master’s degree from the National University of Science and Technology (NUST), Islamabad. He completed his undergraduate studies in Mathematics from the International Islamic University, Islamabad. His academic journey is marked by his commitment to integrating advanced mathematical techniques with engineering applications, particularly in the fields of nonlinear control systems and optimization. Mr. Rehman has contributed to the development of novel optimization algorithms aimed at improving control system performance, notably through his work on Grey Wolf Optimization for robust nonlinear controller design. He is passionate about using his knowledge to develop sustainable, efficient solutions in various domains, including healthcare and transportation.
Professional Profile:
👩🎓Education:
- Master of Science in Computational Sciences and Engineering
- Institution: National University of Science and Technology (NUST), Islamabad
- Duration: September 2021 – August 2023
- CGPA: 3.70 / 4.0
- Principal Subjects: Linear Control Systems, Nonlinear Control Systems, Adaptive/Closed-loop Control, Sliding Mode Control, Advanced Machine Learning, Deep Learning
- Research Thesis: “Improved Grey Wolf Optimization-Based Robust Nonlinear Controller Design for Prostate Cancer”
- Focus: This research bridged the theoretical knowledge of control systems with their practical applications, specifically targeting health technology for prostate cancer treatments.
- Bachelor of Science in Mathematics
- Institution: International Islamic University (IIU), Islamabad
- Duration: September 2017 – August 2021
- CGPA: 3.61 / 4.0
- Principal Subjects: Calculus, Linear Algebra, Real Analysis, Numerical Methods, Partial Differential Equations, Fluid Mechanics, Discrete Structures
🏢 Professional Experience:
Mr. Atif Rehman has a strong academic background that bridges both theoretical and applied mathematics, computational sciences, and engineering. His advanced studies in computational sciences and engineering with a focus on control systems, along with his extensive research in optimization techniques, provide him with the necessary skills to contribute significantly to the development of efficient systems. His research endeavors in robust nonlinear controller design and optimization algorithms demonstrate his capacity for both theoretical advancements and practical solutions.
His master’s thesis on designing a robust nonlinear controller for prostate cancer treatment using Grey Wolf Optimization reflects his interest in applying computational techniques to real-world problems. Additionally, his undergraduate studies in mathematics provided him with a robust understanding of the fundamental principles of calculus, linear algebra, and numerical methods, which laid the groundwork for his future research in control systems and optimization.
Research Interests:
Mr. Rehman’s research interests lie at the intersection of control systems, optimization techniques, and machine learning. Specifically, he is keen on the following areas:
- Deep Reinforcement Learning: Applying reinforcement learning to optimize control systems.
- Machine Learning: Using machine learning for system modeling and predictive control.
- Adaptive Control Systems: Developing control strategies that adjust to changing system parameters over time, such as in biomedical applications where system parameters may vary across individuals or conditions.
- Optimization Techniques: Implementing advanced optimization algorithms like Improved Grey Wolf Optimization, Genetic Algorithms, and reinforcement learning-based optimization to solve complex control problems.
Author Metrics:
- Publications:
- Improved Grey Wolf Optimization-Based Robust Nonlinear Controller Design for Prostate Cancer
- Optimized Nonlinear Robust Controller Along with Model-Parameter Estimation for Blood Glucose Regulation in Type-1 Diabetes
- His works primarily focus on optimization techniques, machine learning, and adaptive control, showing substantial contributions to both academia and practical applications.
- Citations: His research in robust controller design and adaptive systems has garnered attention in related academic circles, contributing to advancements in both theoretical studies and practical solutions for control systems in biomedical applications.