Wanxin Jin (靳万鑫)

I am an Assistant Professor in the Ira A. Fulton Schools of Engineering at Arizona State University. I lead the Intelligent Robotics and Interactive Systems (IRIS) Lab. I teach robotics courses at ASU.

From July 2021 to July 2023, I was a Postdoctoral Researcher in the GRASP Lab, University of Pennsylvania, working with Dr. Michael Posa. I obtained my Ph.D. from Purdue University in 2021, working with Dr. Shaoshuai Mou. I was a research assistant at Technical University of Munich in 2016 and 2017, working with Dr. Sandra Hirche.


My Research

The research of our Intelligent Robotics and Interactive Systems (IRIS) Lab is focused on

  • Human robot alignment: We develop methods to empower a robot with the ability to efficiently understand and be understood by human users through a variety of physical interactions. We explore how robots can aptly respond to and collaborate meaningfully with users.

  • Robot manipulation: We leverage physical principles to derive representations/models that enable robots to interact efficiently with their surroundings. We develop algorithms to enable robots manipulate objects through contact efficiently and robustly.

  • Fundamental methods in robotics: We focus on developing fundamental theories and algorithms for achieving efficient, safe, and robust robot intelligence. Our methods lie at the intersection of model-based (control and optimization) and data-driven approaches, harnessing the complementary benefits of both.

Highlighted Research and Publications

1. Multi-contact manipulation

Task-Driven Hybrid Model Reduction for Dexterous Manipulation
Wanxin Jin and Michael Posa
IEEE Transactions on Robotics (T-RO), 2024
[PDF]/ [Code]/ [Video]/ [Webpage]

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
[PDF]/ [Code]/ [Video]/ [Webpage]

Learning Linear Complementarity Systems
Wanxin Jin, Alp Aydinoglu, Mathew Halm, and Michael Posa
Learning for Dynamics and Control (L4DC), 2022
[PDF] / [Code]

Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics
Shenao Zhang, Wanxin Jin, Zhaoran Wang
International Conference on Machine Learning (ICML), 2023

2. Human-robot alignment

Learning from Human Directional Corrections
Wanxin Jin, Todd D Murphey, and Shaoshuai Mou
IEEE Transactions on Robotics (T-RO), 2022
[PDF] / [Code] / [Videos]

Learning from Sparse Demonstrations
Wanxin Jin, Todd D Murphey, Dana Kulic, Neta Ezer, and Shaoshuai Mou
IEEE Transactions on Robotics (T-RO), 2022
[PDF]/ [Code] / [Videos]

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
[PDF] / [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
[PDF] / [Code]

3. Fundamental Research

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
[PDF] / [Code] / [Videos] [Webpage]

Safe Pontryagin Differentiable Programming
Wanxin Jin, Shaoshuai Mou, and George J. Pappas
Advances in Neural Information Processing Systems (NeurIPS), 2021
[PDF] / [Code] / [Videos] [Webpage]

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
[PDF] / [Videos]

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