Prof Yun-hui Liu

Prof. Yun-hui Liu

Choh-Ming Li Professor of Mechanical and Automation Engineering
Director of CUHK T Stone Robotics Institute (CURI)
Director of Hong Kong Centre for Logistics Robotics

The Chinese University of Hong Kong
 
Biography
Yun-hui Liu received B. Eng. degree in Applied Dynamics from Beijing Institute of Technology, M. Eng. degree in Mechanical Engineering from Osaka University, and Ph.D. degree in Applied Mathematics from the University of Tokyo. After working at the national Electrotechnical Laboratory of Japan as a Research Scientist, he joined The Chinese University of Hong Kong (CUHK) and is currently a Choh-Ming Li Professor of Mechanical and Automation Engineering, the Director of the CUHK T Stone Robotics Institute, and the Director/CEO of Hong Kong Centre for Logistics Robotics funded by the InnoHK clusters of the HKSAR government. He has published more than 500 papers in refereed journals and conference proceedings and was listed in the Highly Cited Authors (Engineering) by Thomson Reuters. His research interests include vision-based robotics, machine intelligence and their applications in manufacturing, logistics, healthcare and constructions. Prof. Liu has received numerous research awards from international journals and international conferences in robotics and automation, and from government agencies. In recent years, he has been actively transferring robotics technologies developed at university labs to industries, and co-founded VisionNav Robotics, CornerStone Robotics, etc. He was the Editor-in-Chief of Robotics and Biomimetics and served as an Associate Editor of the IEEE Transactions on Robotics and Automation. He is Fellow of IEEE, HKIE and HKAE.

Title
Towards AI-Powered Robotic Surgery

Abstract
Robots have been widely used to help surgeons in various surgical procedures. Existing surgical robots are controlled by surgeons via control interfaces. Human control may cause concerns like surgeon-dependent performance/quality, safety risk due to fatigue, etc. The rapid development of AI, in particular embodied AI, presents a lot of opportunity for introducing AI-powered perception and automation to robotic surgery, which would reduce the workload of surgeons, maintain consistence in surgical outcomes, and improve the quality of operations. In this talk, we will introduce our on-going project: AI-powered Surgical Robots, funded by the RGC Area of Excellence Scheme, which aims to develop AI-powered technologies for surgical scene recognition, surgical skill learning, planning and control, and integrated surgical robots with high-level autonomy.