Jinwei Sun

Papers

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About

Jinwei Sun is a leading researcher at the intersection of acoustic signal processing and rehabilitation robotics, whose work is shaping the future of human-robot interaction. His primary research areas include direction-of-arrival (DOA) estimation, sparse Bayesian learning (SBL), and surface electromyography (sEMG)-driven control systems. Sun’s major contributions lie in developing advanced algorithms for robot audition—particularly his 2021 work on acoustic DOA estimation using space alternating SBL, which has garnered 22 citations for its innovative solution to array aperture constraints on humanoid robots and drones. He also pioneered a three-step SBL-based method for room impulse response reconstruction, enabling more accurate time-of-arrival and DOA estimation in complex acoustic environments. In rehabilitation robotics, Sun’s 2024 paper on plug-and-play sEMG-driven hand gesture recognition with subdomain adaptation addresses the critical challenge of cross-user variability, achieving robust performance for exoskeleton gloves. His work bridges theoretical signal processing with practical applications, earning recognition for its impact on autonomous systems and assistive technology. With a growing citation record, Sun continues to push boundaries in making robots more perceptive and rehabilitation tools more adaptive.