Syed Sohaib Ali Shah

National University of Sciences and Technology

Papers

Total Citations

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About

Syed Sohaib Ali Shah is a researcher at the intersection of robotics, computer vision, and rehabilitation engineering. His work focuses on enabling intelligent robotic systems to perceive and interact with dynamic environments, as well as developing assistive technologies for human recovery. His most cited paper, "Ball Detection and Tracking Through Image Processing Using Embedded Systems" (2018, 9 citations), addresses a fundamental challenge in robotics: accurately detecting and tracking a tennis ball in complex scenes. By implementing an image-processing algorithm on embedded systems, Shah’s approach mitigates false detections caused by cluttered backgrounds, improving robot precision—a critical step for applications in sports robotics and autonomous navigation. More recently, his 2025 paper, "Inverse Dynamics Solution of an Upper Limb Rehabilitation Robot Using Deep Learning," (2 citations) pioneers the use of deep learning to solve inverse dynamics for rehabilitation robots, offering a data-driven alternative to traditional analytical methods. This work promises to enhance the adaptability and control of robotic exoskeletons, directly impacting patient recovery outcomes. Shah’s contributions bridge practical embedded systems with cutting-edge AI, demonstrating a clear trajectory from foundational perception tasks to advanced human-robot interaction. His research holds significant promise for both industrial automation and clinical rehabilitation.