About Me

I am a last-year PhD candidate in the Stanford AI Lab, interested in robot learning, perception, and controls.

Email: michellelee@cs.stanford.edu

Twitter: michellearning

Gates Computer Science Building, Room 132
353 Serra Mall, Stanford University
Stanford, CA 94305-9025, USA

Recent News

Invited Talks

Publications

  1. Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks

    Michelle A. Lee*, Yuke Zhu*, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, Jeannette Bohg

    IEEE International Conference on Robotics and Automation (ICRA), May 2019

    Best Paper Award in ICRA 2019

    Finalist for Best Paper in Cognitive Robotics in ICRA 2019.

    [Paper] [Website] [Video] [Code and Dataset]

  2. Variable Impedance Control in End-Effector Space: An Action Space for Reinforcement Learning in Contact-Rich Tasks

    Roberto Martín-Martín, Michelle A. Lee, Rachel Gardner, Silvio Savarese, Jeannette Bohg, Animesh Garg

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019

    [Paper] [Website] [Video]

  3. Making sense of vision and touch: Learning multimodal representations for contact-rich tasks

    Michelle A. Lee, Yuke Zhu, Peter Zachares, Matthew Tan, Krishnan Srinivasan, Silvio Savarese, Li Fei-Fei, Animesh Garg, Jeannette Bohg

    IEEE Transactions on Robotics, March 2020

    [Paper] [Code and Dataset]

  4. Guided Uncertainty Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning

    Michelle A. Lee*, Carlos Florensa*, Jonathan Tremblay, Nathan Ratliff, Animesh Garg, Fabio Ramos, and Dieter Fox

    IEEE International Conference on Robotics and Automation (ICRA), May 2020

    Best Paper Award at the NeurIPS Robot Learning Workshop 2019

    [Paper] [Website] [Video]

  5. Multimodal Sensor Fusion with Differentiable Filters

    Michelle A. Lee*, Brent Yi*, Roberto Martín-Martín, Silvio Savarese, Jeannette Bohg

    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020

    [Paper] [Website] [Code]

  6. Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors

    Michelle A. Lee, Matthew Tan, Yuke Zhu, Jeannette Bohg

    IEEE International Conference on Robotics and Automation (ICRA), June 2021

    [Paper] [Website]

  7. Interpreting Contact Interactions to Overcome Failure in Robot Assembly Tasks

    Peter A. Zachares, Michelle A. Lee, Wenzhao Lian, Jeannette Bohg

    IEEE International Conference on Robotics and Automation (ICRA), June 2021

    [Paper]

  8. Differentiable Factor Graph Optimization for Learning Smoothers

    Brent Yi, Michelle A. Lee, Alina Kloss, Roberto Martín-Martín, Jeannette Bohg

    Submitted to IROS 2021

Teaching


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