Xiao-Hu Zhou

Shandong Institute of Automation, University of Chinese Academy of Sciences

Papers

Total Citations

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About

Xiao-Hu Zhou is a researcher working at the intersection of medical robotics, computer vision, and human-robot interaction, with a particular focus on advancing surgical intelligence and immersive robotic systems. His most influential contribution, "SurgiNet" (2021), demonstrates his expertise in deep learning applied to surgical contexts — specifically developing pyramid attention aggregation and class-wise self-distillation techniques for accurate surgical instrument segmentation, a critical capability for autonomous and semi-autonomous surgical robotics. This work has garnered 55 citations, reflecting its significance to the surgical AI community. Earlier in his career, Zhou contributed to the design and control of a 7-degrees-of-freedom haptic interface (2017), addressing fundamental challenges in human-robot interaction for applications spanning medical simulation, virtual assembly, and remote manipulation. This foundational work reveals his broad engineering background and long-standing interest in bridging physical and virtual environments through intuitive robotic interfaces. Together, Zhou's research trajectory charts a course from haptic hardware innovation toward sophisticated perception algorithms for surgical robotics, positioning him as a meaningful contributor to the development of intelligent, human-centered medical robotic systems.