Haonan Chen

I am a Ph.D. candidate in ECE at the University of Illinois Urbana-Champaign. My research interests focus on learning structured models for robotic manipulation. I am fortunate to be advised by Katie Driggs-Campbell and work closely with Yunzhu Li.

I have conducted extensive research in pushing new capabilities for robotics using machine learning.

Email / CV / Google Scholar

News

I'm co-organizing the Learning Meets Model-Based Methods for Contact-Rich Manipulation workshop at ICRA 2025.
I will be giving a talk at Professor Animashree Anandkumar's Lab at Caltech in April 2025 on "Deployable Robot Learning from Human Priors".
I will be giving a talk at Professor Katerina Fragkiadaki's Lab at Carnegie Mellon University in April 2025 on "Deployable Robot Learning from Human Priors".
I will be giving at the Safe AI Lab at Carnegie Mellon University in March 2025 on "Building Deployable and Pragmatic Robots from Human Priors".
I will be giving at the Parasol Lab at the University of Illinois Urbana-Champaign in March 2025 on "Tool-as-Interface: Learning Robot Policies from Human Tool Usage through Imitation Learning".

Research

My research focuses on robotic manipulation, imitation learning, and human-robot interaction. I develop algorithms that enable robots to learn from human demonstrations and improve their manipulation skills in complex environments.

	Tool-as-Interface: Learning Robot Policies from Human Tool Usage through Imitation Learning H. Chen, C. Zhu, Y. Li, K. Driggs-Campbell Under Review, 2025 Project & Video / Paper Best Presentation Award at CSLSC 2025
	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
	Cooperative Advisory Residual Policies for Congestion Mitigation A. Hasan, N. Chakraborty, H. Chen, J.-H. Cho, C. Wu, K. Driggs-Campbell ACM Journal on Autonomous Transportation Systems (JATS), 2024 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
	Predicting Object Interactions with Behavior Primitives: An Application in Stowing Tasks H. Chen, Y. Niu, K. Hong, S. Liu, Y. Wang, Y. Li, K. Driggs-Campbell Conference on Robot Learning (CoRL), 2023 Project & Video / Paper Finalist - Best Paper/Best Student Paper Awards
	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 Best Presentation Award at CSLSC 2024
	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
	Learning to Navigate Intersections with Unsupervised Driver Trait Inference S. Liu, P. Chang, H. Chen, N. Chakraborty, K. Driggs-Campbell IEEE International Conference on Robotics and Automation (ICRA), 2022 Paper / Website / Video
	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

Service and Leadership

Robotics Seminar @ Illinois
Organizer August 2023 - Present
Coordinated Science Laboratory Student Conference
Organizer 2024

Professional Service

Session Chair:
- CASE - IEEE Conference on Automation Science and Engineering, 2023
Reviewer:
- CoRL - Conference on Robot Learning
- ICRA - IEEE International Conference on Robotics and Automation
- ITSC - IEEE International Conference on Intelligent Transportation Systems
- CASE - IEEE Conference on Automation Science and Engineering

Extra-Curricular Service

Founding Team Leader, Robotic Team for RoboMaster Challenge, ZJU-UIUC Institute 10/2017 - 06/2018

Thanks Jon Barron for this amazing template.