I am a second-year Ph.D. student at University of California, Berkeley, working with Prof. Masayoshi Tomizuka. I am also a part-time AI resident at X, the moonshot factory (formerly Google[x]). My current research interests lie at designing reward learning algorithms to make the robot better interact with the environment.
Before coming to UC Berkeley, I received my B.S. degree from Shanghai Jiao Tong University in 2019. During my undergraduate years, I was fortunate to work with Cewu Lu at SJTU, Jiajun Wu and Josh Tenenbaum at MIT.
Learning dense reward for contact-rich manipulation tasks.
Zheng Wu, Wenzhao Lian, Vaibhav Unhelkar, Masayoshi Tomizuka, Stefan Schaal
Submitted to the International Conference on Robotics and Automation (ICRA), 2021
Efficient sampling-based maximum entropy inverse reinforcement learning with application to autonomous driving.
Zheng Wu*, Liting Sun*, Wei Zhan, Chenyu Yang, Masayoshi Tomizuka (* denotes equal contribution)
IEEE Robotics and Automation Letters (RA-L)
Expressing diverse human driving behavior with probabilistic rewards and online inference.
Liting Sun*, Zheng Wu*, Hengbo Ma, Masayoshi Tomizuka (* denotes equal contribution)
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
See, feel, act: Hierarchical learning for complex manipulation skills with multisensory fusion.
Nima Fazeli , Miquel Oller, Jiajun Wu, Zheng Wu, Joshua B Tenenbaum, Alberto Rodriguez
Paper / Video / MIT News / BBC / CNN
Learning to describe scenes with programs.
Yunchao Liu, Zheng Wu, Daniel Ritchie, William T. Freeman, Joshua B Tenenbaum, Jiajun Wu
International Conference on Learning Representations (ICLR), 2019
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters.
Zheng Wu, Ruiheng Chang, Jiaxu Ma, Cewu Lu, Chi-Keung Tang
International Joint Conference on Artificial Intelligence (IJCAI), 2018
Paper / Slides