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Michael Yip

Associate Professor, Electrical and Computer Engineering

Reinforcement Learning for Robots; Computationally Efficient Robot Planning; Robot Manipulation in Dynamic Environments; Autonomous Robotic Surgery; Mechanical Design of Surgical Robots; Continuum and Snake-like Robots; Artificial Muscles

Michael Yip’s research focus is on developing high-performance robotics that achieve dexterous and agile behaviors. This falls into three categories: (i) flexible robotics, (ii) surgical robotics, and (iii) robotic actuators and biomimetics. He investigates the design and control of flexible robotics, or snake-like robotics, for a broad range of medical, industrial, and military applications. Another significant research effort is in designing surgical robots to treat diseases such as heart disease and prostate cancer, including image-guidance and augmented reality for surgeons to guide them during an operation. A third area of research involves the design of robotic actuators and robotic limbs that mimic natural movement; this includes low-cost artificial muscles that have been used to design robot prostheses or animatronics limbs, and could be used for human augmentation.

Capsule Bio:

Michael Yip is an Assistant Professor of Electrical and Computer Engineering at UC San Diego, IEEE RAS Distinguished Lecturer, Hellman Fellow, and Director of the Advanced Robotics and Controls Laboratory (ARCLab). His group currently focuses on solving problems in data-efficient and computationally efficient robot control and motion planning through the use of various forms of learning representations, including deep learning and reinforcement learning strategies. His lab applies these ideas to surgical robotics and the automation of surgical procedures.

Previously, Yip's research has investigated different facets of model-free control, planning, haptics, soft robotics and computer vision strategies, all towards achieving automated surgery. Yip's work has been recognized through several best paper awards at ICRA, including the 2016 best paper award for IEEE Robotics and Automation Letters. Yip has previously been a research associate with Disney Research in Los Angeles involved in animatronics design, and most recently held a visiting research position with Amazon Robotics Machine Learning and Computer Vision group in Seattle. He received a B.Sc. in Mechatronics Engineering from the University of Waterloo, an M.S. in Electrical Engineering from the University of British Columbia, and a Ph.D. in Bioengineering from Stanford University.

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