Michael Yip, Ph.D.
yip at ucsd.edu | Office: 6121 Atkinson Hall | Ph: 858 822 4778  

Note: Machine Learning / Data Sciences (MLDS) Advising Hours: Thursdays 9:00am - 10:00am
(exception: no office hours on 11/8)

Welcome! I direct the Advanced Robotics and Controls Laboratory (ARCLab). We have two primary areas of research: (i) learning representations for robot control, planning and task automation, and (ii) mechatronic design and control of novel medical robotic devices and algorithms.  On the right side are lists of research interests and applications we are engaged in.

I currently teach two courses at UCSD:
Robot Reinforcement Learning (ECE276C) - senior graduate level course on reinforcement learning for solving robotics and AI problems, with focus on state-of-art algorithms.
Fast Prototyping (ECE115) - junior undergraduate course on mechatronics prototyping from design conception to final product.

Research descriptions: here
Publications: Google Scholar

Short Bio

Academic Position
Assistant Professor, UCSD Electrical and Computer Engineering
Affiliate Faculty, UCSD Mechanical and Aerospace Engineering
Affiliate Faculty, UCSD Artificial Intelligence Group 
Faculty, UCSD Contextual Robotics Institute

Ph.D., Stanford University (Bioengineering)
M.Sc., University of British Columbia (Electrical Engineering)
B.Sc., University of Waterloo (Mechatronics Engineering)

Other Positions
Imagineer (Research Associate), Disney Research, 2014
Research Assistant, Harvard University, 2008
Research Assistant, Massachusetts Institute of Technology, 2007
Research Assistant, Massachusetts General Hospital, 2006

Select Awards
Hellman Fellow, 2017
Outstanding Researcher Award, NIH Center for Simulation in Rehab. Research 2017
Inaugural Best Paper Award, IEEE Robotics and Automation Letters, 2017
Best Paper Finalist, Int. Conf. on Robotics and Automation (ICRA) 2015
Best Paper Award for Advances in Flexible Robotics for Medical Interventions, Int.
Conf. on Robotics and Automation (ICRA) 2014

Academic Service
Robotics, Science, and Systems (RSS), Primary Area Chair
Associate Editor, IEEE Robotics and Automation Letters (RA-L)
Associate Editor, IEEE International Conference on Robotics and Automation (ICRA)
IEEE Haptics Symposium, Sponsorship Chair NSF Panel Reviewer – National Robotics Initiative 2.0
Contributing Author, US Congressional Robotics Roadmap 2016

Areas of Research

  • Machine Learning for robot control, motion planning, task automation
  • Deep Learning and Reinforcement Learning
  • Continuum and Snake-like Robotics
  • Artificial muscles for robotics
  • Image processing and augmented reality

Technical Interests

  • Reinforcement Learning
  • Robot Motion Planning
  • Robot Manipulation
  • Model-Free Control
  • Image Reconstruction and Registration
  • Augmented Reality Interfaces
  • Robot Design

Active Application Areas

  • Computationally Fast and Lightweight Learning, Planning and Control of Robot
  • Reinforcement Learning of Autonomous Assistants for Surgery
  • 3D Visual SLAM for Surgery
  • Robot muscles for biomimetic robots, active prosthetics and orthotics.