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About

Xiaopei Liu is a leading researcher at the intersection of robotics, fluid dynamics, and artificial intelligence, with a primary focus on advancing bio-mimetic underwater robots. His work centers on developing intelligent, agile control systems for fish-like robots, moving beyond traditional methods to harness the full potential of hydrodynamics. Liu’s major contributions include pioneering model-free, end-to-end learning frameworks that enable robotic fish to achieve agile swimming and complex maneuvers without relying on pre-programmed Central Pattern Generators (CPGs). His research also explores how these robots can adapt their control policies to altered background flows, significantly improving their real-world performance and maneuverability. To accelerate this field, Liu developed FishGym, a high-performance physics-based simulation framework for underwater robot learning, which has garnered 22 citations since 2022. His work on creating fluid-interactive virtual agents for digital twin systems further extends his impact, enabling more realistic and interactive simulations. With a growing citation record, Liu’s innovative approaches are setting new standards for autonomous underwater vehicles, promising transformative applications in exploration, environmental monitoring, and beyond.