Mohammad Tabrez Quasim

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About

Dr. Mohammad Tabrez Quasim is a leading researcher at the intersection of artificial intelligence, robotics, and healthcare technology. His work focuses on developing intelligent autonomous systems, with a particular emphasis on deep learning and computer vision for mobile robot control. Dr. Quasim’s most impactful contributions address critical real-world challenges, most notably demonstrated in his highly cited 2021 paper on “Intelligent Autonomous-Robot Control for Medical Applications” (19 citations), which proposed robotic solutions for pandemic-era healthcare shortages. He has pioneered advanced control architectures, including a CNN-PID hybrid system for computer-vision-based mobile robots (16 citations) and deep learning controllers for line-follower robots (13 citations). His 2022 work on “Deep Learning Control for Autonomous Robot” (7 citations) further explores the transformative societal impact of autonomous vehicles. Collectively, his research has garnered over 55 citations, establishing him as an influential voice in autonomous systems engineering. Dr. Quasim’s work is particularly notable for bridging theoretical deep learning advances with practical, deployable solutions in medical robotics and self-driving technology—areas poised to revolutionize both healthcare and transportation.