Shanghai Qi Zhi Institute PI, Assistant Professor at IIIS, Tsinghua.
XU Huazhe is currently a tenure-track Assistant Professor at the Institute for Interdisciplinary Information Sciences, Tsinghua University. He completed his postdoctoral work at Stanford University and earned his Ph.D. from the University of California, Berkeley. In 2021, he served as a part-time visiting scientist in the Meta Artificial Intelligence research department. His research focuses on the theory, algorithms, and applications of embodied artificial intelligence (Embodied AI), including deep reinforcement learning, robotics, and sensorimotor control. He systematically studies visual deep reinforcement learning, imitation learning, and robot manipulation, with the aim of addressing core issues such as low data efficiency and weak generalization ability in embodied artificial intelligence. He has published over 30 top-tier conference papers, and his representative works have been covered by media outlets such as MIT Tech Review and Stanford HAI.
Embodied AI and Robotics
Robotic manipulation and motion control
Reinforcement Learning
Generalizable and sample efficient reinforcement learning
Imitation Learning
Efficient and generalizable imitation learning algorithm
19. Changyi Lin, Han Zhang, Jikai Xu, Lei Wu, Huazhe Xu, 9DTact: A Compact Vision-Based Tactile Sensor for Accurate 3D Shape Reconstruction and Generalizable 6D Force Estimation, IEEE Robotics and Automation Letters (RA-L), 2023 查看PDF
18. Zhecheng Yuan*, Sizhe Yang*, Pu Hua, Can Chang, Kaizhe Hu, Huazhe Xu, RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization, Conference on Neural Inforation Processing Systems (NeurIPS), 2023 查看PDF
17. Ruijie Zheng, Xiyao Wang, Yanchao Sun, Shuang Ma, Jieyu Zhao, Huazhe Xu+, Hal Daumé III+, Furong Huang+, TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
16. Jialu Gao*, Kaizhe Hu*, Guowei Xu, Huazhe Xu, Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning?, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
15. Sizhe Yang*, Yanjie Ze*, Huazhe Xu, MoVie: Visual Model-Based Policy Adaptation for View Generalization, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
14. Yanjie Ze, Yuyao Liu*, Ruizhe Shi*, Jiaxin Qin, Zhecheng Yuan, Jiashun Wang, Huazhe Xu, H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
13. Jinxin Liu*, Li He*, Yachen Kang, Zifeng Zhuang, Donglin Wang, Huazhe Xu, CEIL: Generalized Contextual Imitation Learning, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
12. Yuerong Li, Zhengrong Xue, Huazhe Xu, OTAS: Unsupervised Boundary Detection for Object-Centric Temporal Action Segmentation, IEEE Winter Conference on Applications of Computer Vision (WACV), 2023 查看PDF
11. Nicklas Hansen*, Zhecheng Yuan*, Yanjie Ze*, Tongzhou Mu*, Aravind Rajeswaran+, Hao Su+, Huazhe Xu+, Xiaolong Wang+. On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline, International Conference on Machine Learning (ICML), 2023 查看PDF
10. Zhengrong Xue, Zhecheng Yuan, Jiashun Wang, Xueqian Wang, Yang Gao, Huazhe Xu. USEEK: Unsupervised SE(3)-Equivariant 3D Keypoints for Generalizable Manipulation, International Conference on Robot Automation (ICRA), 2023 查看PDF
9. Changyi Lin, Ziqi Lin, Shaoxiong Wang, Huazhe Xu. DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness, International Conference on Robot Automation (ICRA), 2023 查看PDF
8. Ray Chen Zheng*, Kaizhe Hu*, Zhecheng Yuan, Boyuan Chen, Huazhe Xu. Extraneousness-Aware Imitation Learning, International Conference on Robot Automation (ICRA), 2023 查看PDF
7. Yunfei Li*, Chaoyi Pan*, Huazhe Xu, Xiaolong Wang, Yi Wu. Efficient Bimanual Handover and Rearrangement via Symmetry-Aware Actor-Critic Learning, International Conference on Robot Automation (ICRA), 2023 查看PDF
6. Kaizhe Hu*, Ray Zheng*, Yang Gao, Huazhe Xu. Decision Transformer under Random Frame Dropping, International Conference on Learning Representation (ICLR), 2023 查看PDF
5. Pu Hua, Yubei Chen+, Huazhe Xu+. Simple Emergent Action Representations from Multi-Task Policy Training, International Conference on Learning Representation (ICLR), 2023 查看PDF
4. Linfeng Zhao, Huazhe Xu, Lawson L.S. Wong. Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation, International Conference on Learning Representation (ICLR), 2023 查看PDF
3. Ruijie Zheng*, Xiyao Wang*, Huazhe Xu, Furong Huang, Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function, International Conference on Learning Representation (ICLR), 2023 查看PDF
2. Zhecheng Yuan, Zhengrong Xue, Bo Yuan, Xueqian Wang, Yi Wu, Yang Gao, Huazhe Xu, Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning, Conference on Neural Information Processing Systems (NeurIPS), 2022 查看PDF
1. Can Chang, Ni Mu, Jiajun Wu, Ling Pan, Huazhe Xu, E-MAPP: Efficient Multi-Agent Reinforcement Learning with Parallel Program Guidance, Conference on Neural Information Processing Systems (NeurIPS), 2022 查看PDF
