My research focuses on robotic manipulation, where I develop structured models that help robots reason about the physical world, predict outcomes, and act robustly in unstructured environments.
I aim to equip robots with new capabilities by learning from heterogeneous data sources, including simulation, teleoperation, human video, off-policy data, and synthetic content.
My work has been recognized with a Best Paper Finalist at CoRL 2023 and a Best Paper Award at the ICRA 2025 Workshop on Foundation Models and NeSy AI.
I'm open to potential collaborations. If you see any overlap in our research interests, please feel free to drop me an email.
[2025/06] Invited Talk at Tacta Systems on "Learning What, How, and Where from Humans: Structured Inductive Biases for Robot Learning"
[2025/06] Invited Talk at Professor Jiajun Wu's Lab at Stanford on "Learning What, How, and Where from Humans: Structured Inductive Biases for Robot Learning"
Towards Uncertainty Unification: A Case Study for Preference Learning
S. Peng,
H. Chen,
K. Driggs-Campbell Robotics: Science and Systems (RSS) , 2025
Paper
Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models
H. Chen, J. Xu*, L. Sheng*,
T. Ji,
S. Liu,
Y. Li,
K. Driggs-Campbell IEEE International Conference on Robotics and Automation (ICRA), 2025
Project & Video / Paper
Lessons in Cooperation: A Qualitative Analysis of Driver Sentiments towards real-time Advisory Systems through a Focus Group User Study A. Hasan,
N. Chakraborty,
H. Chen,
J.-H. Cho,
C. Wu,
K. Driggs-Campbell IEEE Intelligent Transportation Systems Magazine (ITSM), 2024
Paper
Towards Safety of Multi-Level Human-Robot Interaction in Industrial Tasks Z. Huang,
Y. Mun,
H. Chen,
Y. Xie, Y. Niu, X. Li, N. Zhong, H. You,
D.L. McPherson,
K. Driggs-Campbell IEEE Conference on Automation Science and Engineering (CASE), Special Session on Cyberphysical Manufacturing Networks, 2023
Learning Task Skills and Goals Simultaneously from Physical Interaction H. Chen*,
Y. Mun*,
Z. Huang,
Y. Niu, Y. Xie,
D.L. McPherson,
K. Driggs-Campbell IEEE Conference on Automation Science and Engineering (CASE), Special Session on Cyberphysical Manufacturing Networks, 2023
PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systems
A. Hasan,
N. Chakraborty*,
H. Chen*,
J-H. Cho,
C. Wu,
K. Driggs-Campbell IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023
Paper / Website
Combining Model-Based Controllers and Generative Adversarial Imitation Learning for Traffic Simulation H. Chen,
T. Ji,
S. Liu,
K. Driggs-Campbell IEEE International Conference on Intelligent Transportation Systems (ITSC), 2022
Paper
Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control P. Chang,
S. Liu,
H. Chen,
K. Driggs-Campbell IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Paper / Video
Awards and Honors
Conference Travel Award, Graduate College, University of Illinois Urbana-Champaign 2023
Finalist - Best Paper/Best Student Paper Awards, Conference on Robot Learning 2023
Bronze Tablet Award, University of Illinois Urbana-Champaign 2020
Excellent Graduate, Zhejiang University 2020
Student Speaker at Graduation, ZJU-UIUC Institute 2020
Provincial Government Scholarship, Zhejiang Province, China (Top 3%) 2019
Dean's List, University of Illinois Urbana-Champaign 2019
National Scholarship, China (Top 1.8%) 2018
Excellent Undergraduate Scholarship, Zhejiang University (Top 3%) 2018-2019
Academic Excellence Scholarship Award, ZJU-UIUC Institute 2017-2019
Top Ten Social Practice, Zhejiang University (Top 1.5%) 2017