Wenzhao Lian

I am joining Shanghai Jiao Tong University as a Professor in the School of Artificial Intelligence. My research focuses at the intersection of machine learning and robotics, particularly the following area:

  • Robotic manipulation problems including grasping and more dexterous operations (an old photo)
  • Imitation learning and reinforcement learning
  • Simulation-to-Real
  • Statistical inference, large models

    My research aims at artificial general intelligece embodied in the physical world in the long run, while solving real-world problems as we climb the mountain. Prior to the current role, I worked as the Director of Robot Manipulation at Figure AI, a staff research scientist at Google X , now known as Intrinsic, and a senior researcher at Vicarious. I received my Ph.D. in Electrical and Computer Engineering at Duke University in 2015, advised by Dr. Lawrence Carin. I received my Bachelor's Degree in Electrical and Computer Engineering in Shanghai Jiao Tong University in 2011.

    I am looking for talented PhD students, master students, interns, postdocs, engineers, and collaborators who share similar interest and passion in robotics and AI (more details)! Feel free to directly email me at lianwenzhao{AT}gmail{DOT}com.

    Publications

  • Yipai Du, Pokuang Zhou, Michael Yu Wang, Wenzhao Lian, Yu She, Stick Roller: Precise In-Hand Stick Rolling with a Sample-Efficient Tactile Model, Proceedings of International Conference on Intelligent Robots and Systems (IROS), 2024
  • Xinghao Zhu, Wenzhao Lian, Bodi Yuan, Daniel Freeman, Masayoshi Tomizuka, Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spaces, Proceedings of International Conference on Robotics and Automation (ICRA), 2023
  • Achu Wilson, Helen Jiang, Wenzhao Lian, Wenzhen Yuan, Cable Routing and Assembly using Tactile-driven Motion Primitives, Proceedings of International Conference on Robotics and Automation (ICRA), 2023
  • Zheng Wu, Yichen Xie, Wenzhao Lian, Changhao Wang, Yanjiang Guo, Jianyu Chen, Stefan Schaal, Masayoshi Tomizuka, Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning, Proceedings of International Conference on Robotics and Automation (ICRA), 2023
  • Zheng Wu, Wenzhao Lian, Changhao Wang, Mengxi Li, Stefan Schaal, Masayoshi Tomizuka, Prim-LAfD: A Framework to Learn and Adapt Primitive-Based Skills from Demonstrations for Insertion Tasks, IFAC World Congress, 2023
  • Bowen Wen, Wenzhao Lian, Kostas Bekris, Stefan Schaal, You Only Demonstrate Once: Category-Level Manipulation from Single Visual Demonstration, Robotics: Science and Systems (RSS), 2022 (Best Paper Award Finalist)
  • Bowen Wen, Wenzhao Lian, Kostas Bekris, Stefan Schaal, CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from Simulation, Proceedings of International Conference on Robotics and Automation (ICRA), 2022
  • Toki Migimatsu, Wenzhao Lian, Jeannette Bohg, Stefan Schaal, Symbolic State Estimation with Predicates for Contact-Rich Manipulation Tasks, Proceedings of International Conference on Robotics and Automation (ICRA), 2022
  • Wenzhao Lian, Tim Kelch, Dirk Holz, Adam Norton, Stefan Schaal, Benchmarking Off-The-Shelf Solutions to Robotic Assembly Tasks, Proceedings of International Conference on Intelligent Robots and Systems (IROS), 2021
  • Shiyu Jin, Wenzhao Lian, Changhao Wang, Masayoshi Tomizuka, Stefan Schaal, Robotic Cable Routing with Spatial Representation, IEEE Robotics and Automation Letters (RA-L)
  • Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerik, Ning Ye, Stefan Schaal, Jon Scholz, Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study, Robotics: Science and Systems (RSS), 2021
  • Zheng Wu, Wenzhao Lian, Vaibhav Unhelkar, Masayoshi Tomizuka, Stefan Schaal, Learning Dense Rewards for Contact-Rich Manipulation Tasks, Proceedings of International Conference on Robotics and Automation (ICRA), 2021
  • Peter A. Zachares, Michelle A. Lee, Wenzhao Lian, Jeannette Bohg, Interpreting Contact Interactions to Overcome Failure in Robot Assembly Tasks, Proceedings of International Conference on Robotics and Automation (ICRA), 2021
  • Wenzhao Lian, Ricardo Henao, Vinayak Rao, Joseph Locus, Lawrence Carin, A Multitask Point Process Predictive Model,( Appendix ) In Proceedings of the International Conference on Machine Learning, 2015
  • Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin, Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data, ( Appendix ) Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
  • Evan X. Chen, Wenzhao Lian, Lawrence Carin, David Brady, Task-driven Adaptive Sensing on Quadrupole Mass Filter Systems for Classification, Computational Optical Sensing and Imaging, 2015
  • Kyle Ulrich, David Carlson, Wenzhao Lian, Jana Borg, Kafui Dzirasa, Lawrence Carin, Analysis of Brain States from Multi-Region LFP Time-Series, ( Appendix ) Advances in Neural Information Processing Systems, 2014
  • Esther Salazar, Yuliya Nikolova, Wenzhao Lian, Piyush Rai, Adrienne L. Romer, Ahmad R. Hariri, and Lawrence Carin, A Bayesian Framework for Multi-Modality Analysis of Mental Health, ( Appendix ) submitted
  • Piyush Rai, Wenzhao Lian, Lawrence Carin, Bayesian Multitask Distance Metric Learning, NIPS Workshop on Transfer and Multi-Task Learning: Theory meets Practice, 2014
  • Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang, Convex factorization machine for toxicogenomics prediction, Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
  • Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin, Bayesian Multiview Factor Modeling for Integrating and Analyzing Heterogeneous Clinical Data, NIPS Workshop on Machine Learning for Clinical Data Analysis, Healthcare and Genomics, 2014
  • Wenzhao Lian, Vinayak Rao, Brian Eriksson, Lawrence Carin, Modeling Correlated Arrival Events with Latent Semi-Markov Processes, ( Appendix ) (Code) In Proceedings of the International Conference on Machine Learning, 2014
  • Wenzhao Lian, Ronen Talmen, Hitten Zaveri, Lawrence Carin, Ronald Coifman, Multivariate Time-Series Analysis and Diffusion Maps, Signal Processing, 2015, vol. 116, pp. 13-28
  • David E. Carlson, Joshua T. Vogelstein, Qisong Wu, Wenzhao Lian, Mingyuan Zhou, Colin R. Stoetzner, Daryl Kipke, Douglas Weber, David B. Dunson and Lawrence Carin, Sorting Electrophysiological Data via Dictionary Learning & Mixture Modeling, IEEE Transactions on Biomedical Engineering. July, 2013