Usman Ghafoor

Pusan National University, Institute of Space Technology

Papers

Total Citations

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About

Usman Ghafoor is a leading researcher at the intersection of neural engineering and advanced robotics, with a focus on developing intuitive human-machine interfaces and robust control systems. His seminal review, "Motor-commands decoding using peripheral nerve signals," has garnered 63 citations, establishing a foundational framework for neuroprosthetic development by detailing how natural-feeling interfaces can decode neural commands from peripheral nerves to control robotic limbs. This work has been pivotal in advancing the field of neuroprosthetics, bridging the gap between the human nervous system and external devices. More recently, Ghafoor has pioneered robust control strategies for complex robotic systems, as evidenced by his 2023 paper on "DDPG-Based Adaptive Sliding Mode Control with Extended State Observer for Multibody Robot Systems." This work, with 11 citations, introduces a novel hybrid approach combining deep reinforcement learning with sliding mode control to achieve finite-time stability and resilience against uncertainties in multibody robots. His contributions are driving progress in both neural decoding and adaptive control, with significant implications for next-generation prosthetics and autonomous robotic systems.