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About

Kaiyang Yin is a leading researcher at the intersection of bio-inspired robotics, neuromuscular control, and intelligent exoskeleton systems. His work centers on developing adaptive, human-like control strategies for robotic ankle exoskeletons and bipedal robots, drawing inspiration from natural muscle activation and neural feedback mechanisms. Yin’s most influential contribution is his pioneering approach to personalised exoskeleton control, as demonstrated in his highly cited 2019 paper on experience-based adaptive fuzzy inference (37 citations), which moves beyond rigid, model-based schemes to achieve robust, user-specific assistance. He has further advanced the field by introducing virtual neuromuscular control for standing balance (11 citations) and variable impedance control for bipedal robots (8 citations), effectively bridging the gap between human physiology and robotic actuation. Beyond biomechatronics, Yin has made notable contributions to industrial diagnostics, developing a multi-feature fusion method for GIS partial discharge pattern recognition (24 citations). His work on hybrid SEMG and Kinect-based motion identification (3 citations) also showcases his versatility in human-robot interaction. With a growing citation impact exceeding 100, Kaiyang Yin is shaping the future of adaptive, human-centred robotics.