Michael Yip, Ph.D.

Director, Advanced Robotics and Controls Laboratory (ARCLab)

Director, Medical Robotics Collab,  Contextual Robotics Institute

Associate Professor, Electrical and Computer Engineering 

Affiliate Professor, Computer Science and Engineering

Affiliate Professor,  Mechanical and Aerospace Engineering

Affiliate Professor, Artificial Intelligence Group

Office: Franklin Antonio Hall Rm 3202

Tel: (858) 822-4778 

Email:  yip@ucsd.edu 



Machine Learning / Data Sciences Curriculum Office Hours - by email only

Short Bio

Michael Yip, Ph.D., is an Associate Professor at the University of California San Diego and the Director of the Advanced Robotics and Controls Laboratory. His research expertise is at the intersection of robotics, machine learning, and computer vision, enabling robots to work with deformable objects and environments with image guidance and tactile perception. The work has been applied to automating robotic surgery, enabling snake robot locomotion, coordinating multiple robot arms, autonomous driving, and search and rescue. Dr. Yip and his research group have won numerous best paper awards at major robotics conferences and journals. Dr. Yip was previously a Research Associate with Disney Research, a Visiting Professor at Stanford University, and a Visiting Professor of Machine Learning and Computer Vision with Amazon Robotics. He received a B.Sc. from the University of Waterloo, an M.S. from University of British Columbia, and his Ph.D. from Stanford University.

Research 

Robots currently lack a strong set of algorithmic tools to deal with uncertainty and dynamic environments, whether it be in the home, in a semi-automated warehouse, or in a robotic surgical operating room. Unlike the past decade of robot applications that primarily focused on highly repetitive assembly line tasks, the robots of the future will need to interact with new and changing environments. My research interests are in learning-based representations for robots that enable robots to explore and adapt control to new environments and conditions, enabling responsive artificial intelligence, planning, and execution in dynamic environments. These representations are trained using a variety of local and global model-free learning strategies, and when implemented are comparatively significantly faster, more consistent, and more power and memory efficient than state-of-art robots. The problems I am interested in solving are in the general areas of robot manipulation, constrained motion planning, and robotic surgery. Furthermore, as we consider new complex tasks for robots to perform, such as in automating robotic surgery, we come across the need to develop new robotic systems to reach those goals. Thus, a parallel research interest is to develop new, dexterous robot manipulators include snake-like robot platforms and MRI/CT/Ultrasound-safe robotic platforms.


Lab Website

Advanced Robotics and Controls Laboratory (ARCLab)


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Full Address

Atkinson Hall 6121

9500 Gilman Drive MC0436

La Jolla, CA 92093-0436

Tel: (858) 822-4778

Email: yip@ucsd.edu 


Complete CV

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