Junwoo Chang

I am currently a M.S. student at Machine Learning and Control Systems Lab (MLCS) at Yonsei University, advised by Prof. Jongeun Choi. My research interests lie at the intersection of robotics and machine learning, focusing on symmetry-aware reinforcement learning for improved sample efficiency and generalization.

Email / CV / Scholar / Github

Publications

( ^* Equal contribution, ^† Equal advising)

	Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments Junwoo Chang, Minwoo Park, Joohwan Seo, Roberto Horowitz, Jongmin Lee^†, Jongeun Choi^† ICLR 2026 arXiv \| code (TBD)
	Group-Invariant Unsupervised Skill Discovery: Symmetry-aware Skill Representations for Generalizable Behavior Junwoo Chang, Joseph Park, Roberto Horowitz, Jongmin Lee^†, Jongeun Choi^† Preprint (Under Review), 2026 arXiv \| code (TBD)
	Multi-Robot Motion Planning from Vision and Language using Heat-Inspired Diffusion Jebeom Chae^, Junwoo Chang^, Seungho Yeom, Yujin Kim, Jongeun Choi Preprint (Under Review), 2025 arXiv
	Symmetry-Aware Steering of Equivariant Diffusion Policies: Benefits and Limits Minwoo Park^, Junwoo Chang^, Jongeun Choi, Roberto Horowitz Preprint (Under Review), 2025 arXiv
	SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey Joohwan Seo, Soochul Yoo, Junwoo Chang, Hyunseok An, Hyunwoo Ryu, Soomi Lee, Arvind Kruthiventy, Jongeun Choi, Roberto Horowitz, IJCAS 2025 arXiv
	Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation Hyunwoo Ryu, Jiwoo Kim, Hyunseok An, Junwoo Chang, Joohwan Seo, Taehan Kim, Yubin Kim, Chaewon Hwang, Jongeun Choi, Roberto Horowitz, CVPR 2024 (Highlight) webpage \| arXiv \| code
	Denoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planning Junwoo Chang^, Hyunwoo Ryu^, Jiwoo Kim, Joohwan Seo, Nikhil Potu Surya Prakash, Jongeun Choi, Roberto Horowitz, NeurIPS 2023 Workshop on Diffusion Models webpage \| arXiv \| code
Website source code credit to Jon Barron.