Mr Muhammad Shahab, King Fahd University of Petroleum and Minerals, KFUPM, Saudi Arabia
Muhammad Shahab is a motivated robotics and control systems researcher currently pursuing his MSc in System and Control Engineering at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. With a background in Mechatronics Engineering from the University of Engineering and Technology, Peshawar, he has consistently demonstrated a passion for innovation in autonomous systems, fault-tolerant control, and cyber-physical systems. He has contributed to multiple high-impact research projects and publications, particularly in mobile robotics and intelligent control algorithms. His academic journey is marked by scholarships, competitive projects, and technical achievements that reflect his commitment to advancing technology in robotics and automation. With strong programming and problem-solving skills, Muhammad is well-equipped to handle complex engineering challenges. He actively contributes to the academic community through teaching assistantships, publications, and collaborative research. His future vision revolves around developing resilient, adaptive autonomous systems with real-world applications in smart industries and transportation.
Publication Profile
scopus
Education
Muhammad Shahab is currently enrolled in the Master of Science (MSc) program in System and Control Engineering at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, under a fully funded scholarship. His graduate coursework includes advanced subjects such as Linear Multivariable Control, Nonlinear Control, System Identification, Advanced Robotics, and Machine Learning, with a CGPA of 3.607. Earlier, he earned his Bachelor of Science (BSc) in Mechatronics Engineering from the University of Engineering and Technology Peshawar, Pakistan, in 2021 with a CGPA of 3.4. His undergraduate training focused on Mechatronic System Design, Robotics, Control Systems, and Embedded Systems. He was also awarded the Prime Minister’s Laptop for academic excellence. His educational background blends mechanical design, electronics, and intelligent control, forming a strong foundation for robotics and automation research. He has also participated in numerous technical projects, showcasing his practical grasp of engineering systems and real-time implementation.
Experience
Muhammad Shahab has a rich blend of academic and industrial experience. Currently, he is a Teaching Assistant at KFUPM for the course “Path Planning and Navigation for Mobile Robots,” where he supports students with algorithms, assignments, and conceptual understanding. As a Research Assistant at KFUPM, he is working on a review paper related to prognostics and diagnosis of machine tools in Industry 5.0. Previously, he completed internships at three different engineering firms in Pakistan: Mir Engineering Pvt. Ltd., where he worked on solar water systems; Shama Ghee Pvt. Ltd., focusing on boiler house operations and motor maintenance; and Pakistan Locomotive Factory, gaining insights into CNC machining and locomotive systems. Additionally, his undergraduate projects, including a 3D wire bending machine and autonomous vehicle control, reflect a practical grasp of real-world systems. His roles consistently demonstrate a focus on automation, robotics, control, and diagnostics, contributing to both learning and innovation.
Awards and Honors
Muhammad Shahab has received notable academic recognitions throughout his educational journey. At KFUPM, he is a recipient of a fully funded scholarship for his MSc studies in System and Control Engineering, a testament to his academic excellence and research potential. During his undergraduate studies at UET Peshawar, he was awarded the Prime Minister’s Laptop as part of a government merit-based initiative for high-achieving students. Additionally, his Final Year Project, an Automatic 3D Wire Bending Machine, was funded by the National Grassroots ICT Research Initiative (NGIRI) — a prestigious acknowledgment aimed at supporting impactful student innovations in Pakistan. These awards not only underscore his technical competence but also his ability to apply engineering knowledge to real-world problems. His continuous involvement in funded projects and competitive academic environments highlights his dedication to advancing his expertise in robotics, intelligent control systems, and industrial automation.
Research Focus
Muhammad Shahab’s research interests revolve around the intersection of robotics, control theory, and intelligent fault-tolerant systems. His work emphasizes robust and adaptive control for autonomous systems, including mobile robots and self-driving vehicles. He is particularly focused on cyber-physical systems where real-time responsiveness and reliability are critical. His research includes data-driven techniques like Q-learning and machine learning for predictive diagnostics and fault-tolerance, ensuring resilient operation in uncertain environments. His recent contributions explore formation control of wheeled mobile robots, trajectory tracking in autonomous lane changes, and sensor fusion under varying environmental conditions. He also delves into predictive maintenance strategies within the scope of Industry 5.0, contributing to the evolution of smart industrial systems. Through both simulation and hardware-based projects, Muhammad aims to bridge theoretical advancements with practical applications, building systems that are not only autonomous but also intelligent, self-correcting, and suitable for deployment in safety-critical domains like transportation and manufacturing.
Publication Top Notes
📄Particle Swarm Optimization tuned PID Control of Hybrid Renewable Energy-based Multi-area Power System – IEEE CyberScience Congress, 2023
📄 Trajectory Tracking Control for Lane Change Maneuvers in Autonomous Vehicles – ICARCV 2024 (Accepted)
📄 A Data-Driven Fault-Tolerant Approach for Mobile Robots Using Q-Learning and Regression – IEEE Conference (Under Preparation)
📄 Formation Control of Wheeled Mobile Robots with Fault Tolerant Capabilities – Robotics MDPI (Accepted, March 2025)
📄 State of the Art and Future Trends in Predictive Maintenance in the Context of Industry 5.0 – International Journal of Production Research (Under Review)
📄 A Comprehensive Survey on Formation Control of Mobile Robots: From Classical to Intelligent Fault-Tolerant Strategies – Annual Review of Control (Under Preparation)
📄 Impact of Environmental Conditions on Sensor Fusion, Motion Planning, and Control of Autonomous Vehicles – International Journal of Intelligent Transportation Systems Research (Under Review)