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About

Mohammad Sarim is a researcher whose work spans autonomous systems, robotics, and neuromorphic computing, with a particular focus on advancing intelligent navigation technologies for unmanned systems. His most significant contribution, a 2018 comparative study on path-planning and obstacle avoidance algorithms for UAVs, has garnered over 212 citations, establishing him as a notable voice in the rapidly growing field of unmanned aerial vehicle research. This work addressed the critical "Sense and Avoid" challenge, providing the research community with a comprehensive framework for evaluating navigation strategies across diverse real-world scenarios. Beyond UAVs, Sarim has made meaningful strides in bio-inspired robotics. His investigations into neuromorphic computing explore how memristive devices and Spike Timing Dependent Plasticity (STDP) can replicate biological learning mechanisms, enabling robots to navigate autonomously with ultra-low energy consumption. His 2016 work on tilt-rotor quadcopters further demonstrates his hands-on engineering expertise, tackling the under-actuation limitations of conventional drone designs through innovative mechanical solutions. Sarim's research bridges hardware fabrication, control theory, and artificial intelligence, making him a multidisciplinary contributor whose work is particularly relevant for students and engineers interested in the future of autonomous, adaptive robotic systems.