I am studying Electrical Engineering & Computer Science at UC Berkeley. Currently, I'm researching at the Berkeley AUTOLAB and the Berkeley AI Research Lab advised by Prof. Ken Goldberg.
My research interests lie at the intersection of robotics, machine learning and automation.
BAIR Blog on robust imitation learning.
Publications
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A Dynamic Regret Analysis and Adaptive Regularization Algorithm for On-Policy Robot Imitation Learning.
Jonathan Lee, Michael Laskey, Ajay Tanwani, Anil Aswani, Ken Goldberg.
Algorithmic Foundations of Robotics, 2018. -
Constraint Estimation and Derivative-Free Recovery for Robot Learning from Demonstrations.
Jonathan Lee, Michael Laskey, Roy Fox, Ken Goldberg.
IEEE Conference on Automation Science and Engineering (CASE), 2018. -
DART: Noise Injection for Robust Imitation Learning.
Michael Laskey, Jonathan Lee, Roy Fox, Anca Dragan, Ken Goldberg.
Conference on Robot Learning (CoRL), 2017. -
Comparing Human-Centric and Robot-Centric Sample Efficiency for Robot Deep Learning from Demonstrations.
Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin Jamieson, Anca Dragan, Ken Goldberg.
IEEE Conference on Robotics and Automation (ICRA), 2017. -
Robot Grasping in Clutter: Using a Hierarchy of Supervisors for Learning from Demonstrations.
Michael Laskey, Jonathan Lee, Caleb Chuck, David Gealy, Wesley Hsieh, Florian T. Pokorny, Anca D. Dragan, and Ken Goldberg.
IEEE Conference on Automation Science and Engineering (CASE), 2016.
Papers
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Stability Analysis of On-Policy Imitation Learning Algorithms Using Dynamic Regret.
Jonathan Lee, Michael Laskey, Ajay Kumar Tanwani, Ken Goldberg.
RSS Workshop on Imitation and Causality, 2018. -
Iterative Noise Injection for Scalable Imitation Learning.
Michael Laskey, Jonathan Lee, Wesley Hsieh, Richard Liaw, Jeffrey Mahler, Roy Fox, Ken Goldberg.
arXiv, 2017.