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About

Yukai Feng is a leading researcher at the frontier of bio-inspired robotics and intelligent control, with a primary focus on biomimetic robotic fish and their autonomous underwater operations. Feng’s work has fundamentally advanced how these robotic systems learn and cooperate, bridging the gap between biological locomotion and artificial intelligence. His highly cited survey (2023, 34 citations) provides a comprehensive roadmap for applying reinforcement learning to bionic underwater robots, while his subsequent review (2024, 18 citations) synthesizes the latest breakthroughs in design, sensing, and autonomy. Feng’s most innovative contributions lie in multi-agent coordination and skill transfer. He developed a decentralized, attraction-enhanced reinforcement learning framework for multi-robotic fish pursuit control, enabling efficient cooperative behavior without centralized oversight. Furthermore, his pioneering two-stage transfer learning method allows a bionic robotic fish to directly learn swimming skills from real fish, dramatically improving performance through dynamic trajectory control. With a rapidly growing citation impact and papers published in top venues, Feng is recognized as a rising authority in biomimetic robotics, pushing the boundaries of what underwater autonomous systems can achieve through learning from nature.