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About

Hing-Choi Fu is a leading researcher at the intersection of soft robotics and medical intervention, specializing in the development of intelligent, compliant robotic systems for minimally invasive surgery. His major contributions lie in solving the fundamental control challenges of soft continuum robots, which, due to their inherent compliance, are ideal for safe navigation within delicate anatomical environments but notoriously difficult to model and control precisely. Fu pioneered nonparametric online learning control frameworks, most notably using Local Gaussian Process Regression, enabling these robots to adapt their kinematics in real-time through vision-based feedback. This breakthrough, detailed in his highly cited 2017 and 2019 papers (126 and 115 citations respectively), provides an enabling technique for effective endoscopic navigation. Beyond control, he has advanced the field's hardware, designing a spring-reinforced actuator that bridges the gap between soft compliance and high-force performance, and developing a compact hydraulic robot for intraoperative MRI-guided stereotactic neurosurgery. With a cumulative impact of nearly 400 citations on his top works, Fu’s research is pivotal in transforming soft robots from theoretical curiosities into practical, precise tools for life-saving medical procedures.