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Youngwoon Lee

Ph.D. Candidate
University of Southern California

I am currently on the academic job market!

I am a fifth-year Ph.D. student at University of Southern California advised by Joseph J. Lim. My research interests are in deep reinforcement learning, imitation learning, and simulation-to-real transfer for robotics. Particularly, I focus on developing scalable and compositional robot learning algorithms that make robots learn complex long-horizon tasks by incorporating prior knowledge and data.

In Summer 2020, I have interned with Yuke Zhu and Anima Anandkumar at NVIDIA Research. I also have interned at NAVER CLOVA (2021) and SKT T-Brain (2018) over the summers. Before joining USC, I received B.S. and M.S. degrees in computer science from KAIST advised by Sung-Eui Yoon.


  • [May, 2022] I am selected as a 2022 RSS Pioneer
  • [Apr, 2022] I am an invited speaker on the GRASP SFI seminar series at U. Penn
  • [Sep, 2021] One paper is accepted to NeurIPS 2021
  • [Sep, 2021] Three papers are accepted to CoRL 2021
  • [May, 2021] One paper is accepted to RSS 2021
  • [May, 2021] I'm co-organizing the workshop on Combining Learning and Motion Planning at IROS 2021
  • [Feb, 2021] IKEA Furniture Assembly Environment is accepted to ICRA 2021
  • [Nov, 2020] SPiRL won the best paper presentation award at CoRL 2020
  • [Oct, 2020] Two papers are accepted to CoRL 2020
  • [May, 2020] In Summer 2020, I will be a research intern at NVIDIA Research
  • [Dec, 2019] One paper is accepted to ICLR 2020
  • [Nov, 2019] We release IKEA Furniture Assembly Environment for Complex Robot Manipulation Benchmark
  • [Sep, 2019] One paper is accepted to CoRL 2019
  • [Dec, 2018] One paper is accepted to ICLR 2019

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