Below are some representative publications in each research interest. Please visit Publications page for a full list.

Contact-rich manipulation
  • Multi-Contact modeling and simulation
  • Learning, planning, and control for contact-rich manipulation
  • Multisensory perception in dexterous manipulation
TwinTrack: Bridging Vision and Contact Physics for Real-Time Tracking of Unknown Dynamic Objects
Wen Yang, Zhixian Xie, Xuechao Zhang, Heni Ben Amor, Shan Lin, Wanxin Jin
arXiv, 2025
Paper Webpage Video
Complementarity-Free Multi-Contact Modeling and Optimization for Dexterous Manipulation
Wanxin Jin
Robotics: Science and Systems (RSS), 2025
𝕏-Twitter Paper Code Video
ContactSDF: Signed Distance Functions as Multi-Contact Models for Dexterous Manipulation
Wen Yang and Wanxin Jin
IEEE Robotics and Automation Letters (RA-L), 2025
𝕏-Twitter Webpage Paper Code Video
Task-Driven Hybrid Model Reduction for Dexterous Manipulation
Wanxin Jin and Michael Posa
IEEE Transactions on Robotics (T-RO), 2024
Paper Code Video Project
Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning
Wei-Cheng Huang, Alp Aydinoglu, Wanxin Jin, Michael Posa
IEEE International Conference on Robotics and Automation (ICRA), 2024
Paper Video Project
Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
Shenao Zhang, Wanxin Jin, Zhaoran Wang
International Conference on Machine Learning (ICML), 2023
Paper
Learning Linear Complementarity Systems
Wanxin Jin, Alp Aydinoglu, Mathew Halm, and Michael Posa
Learning for Dynamics and Control (L4DC), 2022
Paper Code


Autonomy alignment
  • Learning from demonstrations
  • Learning from interactions
Robust Reward Alignment via Hypothesis Space Batch Cutting
Zhixian Xie, Haode Zhang, Yizhe Feng, Wanxin Jin
International Conference on Machine Learning (ICML), 2025
Paper Code (coming soon) Video (coming soon)
Language-Model-Assisted Bi-Level Programming for Reward Learning from Internet Videos
Harsh Mahesheka, Zhixian Xie, Zhaoran Wang, Wanxin Jin
arXiv preprint, 2024
𝕏-Twitter Paper Video
Safe MPC Alignment with Human Directional Feedback
Zhixian Xie, Wenlong Zhang, Yi Ren, Zhaoran Wang, George. J. Pappas and Wanxin Jin
Submitted to IEEE Transactions on Robotics (T-RO), 2024
𝕏-Twitter Paper Code Video Project
Learning from Human Directional Corrections
Wanxin Jin, Todd D Murphey, Zehui Lu, and Shaoshuai Mou
IEEE Transactions on Robotics (T-RO), 2023
Paper Code Video
Learning from Sparse Demonstrations
Wanxin Jin, Todd D Murphey, Dana Kulic, Neta Ezer, and Shaoshuai Mou
IEEE Transactions on Robotics (T-RO), 2023
Paper Code Video
Inverse Optimal Control from Incomplete Trajectory Observations
Wanxin Jin, Dana Kulic, Shaoshuai Mou, and Sandra Hirche
International Journal of Robotics Research (IJRR), 40:848–865, 2021
Paper Code
Inverse Optimal Control for Multiphase cost functions
Wanxin Jin, Dana Kulic, Jonathan Lin, Shaoshuai Mou, and Sandra Hirche
IEEE Transactions on Robotics (T-RO), 35(6):1387–1398, 2019
Paper Code


Fundamental methods in robotics
  • Optimal control, motion plannig, reinforcement learning
  • Differentiable optimization, inverse optimization
  • Hybrid system learning and control
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework
Wanxin Jin, Zhaoran Wang, Zhuoran Yang, and Shaoshuai Mou
Advances in Neural Information Processing Systems (NeurIPS), 2020
Paper Code Video Project
Safe Pontryagin Differentiable Programming
Wanxin Jin, Shaoshuai Mou, and George J. Pappas
Advances in Neural Information Processing Systems (NeurIPS), 2021
Paper Code Video Project
Robust Safe Learning and Control in Unknown Environments: An Uncertainty-Aware Control Barrier Function Approach
Jiacheng Li, Qingchen Liu, Wanxin Jin, Jiahu Qin, and Sandra Hirche
IEEE Robotics and Automation Letters (RA-L), 2023
Paper Video
Enforcing Hard Constraints with Soft Barriers: Safe-driven Reinforcement Learning in Unknown Stochastic Environments
Yixuan Wang, Simon Sinong Zhan, Ruochen Jiao, Zhilu Wang, Wanxin Jin, Zhuoran Yang, Zhaoran Wang, Chao Huang, Qi Zhu
International Conference on Machine Learning (ICML), 2023
Paper
A Differential Dynamic Programming Framework for Inverse Reinforcement Learning
Kun Cao, Xinhang Xu, Wanxin Jin, Karl H. Johansson, and Lihua Xie
Submitted to IEEE Transactions on Robotics (T-RO), 2024
Paper