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Shanghai Qi Zhi Institute PI, Assistant Professor at IIIS, Tsinghua.
Yang Gao obtained his Ph.D. degree from UC Berkeley, advised by Prof. Trevor Darrell and B.E. from the Computer Science Department at Tsinghua University.
He is interested in the intersection between computer vision and robotics. Specifically, He wants to explore how to utilize the prior knowledge we have from computer vision to do robot manipulation tasks both more efficiently and effectively. This not only involves understanding how to use the previous visual experiences but also potentially needs re-designing robotic learning algorithms to better handles the visual states. Thus, it is a co-design problem between vision and robotics. As testing benchmarks, he works on robot manipulation and autonomous driving applications, both in simulation and in the real world.
Personal honor:
Beijing Talented Youth Program
Robot Learning
study the software behind the general purpose robot
Autonomous Driving
The next-generation vision-centric and data-driven autonomous driving solutions
Research Direction：
Reinforcement learning
Computer vision
robotics
Responsibilities：
1. Responsible for theoretical research, algorithm or system development in the above-mentioned related fields and directions;
2. Publish academic or innovative research results in the above-mentioned related fields.
Qualifications:
1. Computer, electronics, automation, software and other related professional background, strong academic ability;
2. Possess excellent basic theoretical knowledge and programming skills in the field (Python, Linux, C++, etc.);
3. Those who have published papers in top conferences in the above fields are preferred
Please send your CV：
gy20073@gmail.com
23. Kaifeng Zhang, Rui Zhao, Ziming Zhang, Yang Gao, Auto-Encoding Adversarial Imitation Learning, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023 查看PDF
22. Tong Zhang, Yingdong Hu, Hanchen Cui, Hang Zhao, Yang Gao, A Universal Semantic-Geometric Representation for Robotic Manipulation, International Conference on Robots Learning (CORL), 2023 查看PDF
21. Shengjie Wang, Fengbo Lan, Xiang Zheng, Yuxue Cao, Oluwatosin Oseni, Haotian Xu, Tao Zhang, Yang Gao, A Policy Optimization Method Towards Optimal-time Stability, International Conference on Robots Learning (CORL), 2023 查看PDF
20. Jialei Huang, Zhaoheng Yin, Yingdong Hu, Yang Gao, Policy Contrastive Imitation Learning, International Conference on Machine Learning (ICML), 2023 查看PDF
19. Yingdong Hu, Renhao Wang, Li Erran Li, Yang Gao, For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal, International Conference on Machine Learning (ICML), 2023 查看PDF
18. Kaizhe Hu, Ray Chen Zheng, Yang Gao, Huazhe Xu, Decision Transformer under Random Frame Dropping, International Conference on Learning Representation (ICLR), 2023 查看PDF
17. 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
16. Yixuan Mei, Jiaxuan Gao, Weirui Ye, Shaohuai Liu, Yang Gao, Yi Wu, SpeedyZero: Mastering Atari with Limited Data and Time, International Conference on Learning Representation (ICLR), 2023 查看PDF
15. Jiaye Teng, Chuan Wen, Dinghuai Zhang, Yoshua Bengio, Yang Gao, Yang Yuan, Predictive Inference with Feature Conformal Prediction, International Conference on Learning Representation (ICLR), 2023 查看PDF
14. Weirui Ye, Yunsheng Zhang, Pieter Abbeel, Yang Gao, Become a Proficient Player with Limited Data through Watching Pure Videos, International Conference on Learning Representation (ICLR), 2023 查看PDF
13. Renhao Wang, Jiayuan Mao, Joy Hsu, Hang Zhao, Jiajun Wu, Yang Gao, Programmatically Grounded, Compositionally Generalizable Robotic Manipulation, International Conference on Learning Representation (ICLR), 2023 查看PDF
12. Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao, Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming, International Conference on Machine Learning (ICML), 2022 查看PDF
11. 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
10. Jinkun Cao, Ruiqian Nai, Qing Yang, Jialei Huang, Yang Gao, An Empirical Study on Disentanglement of Negative-free Contrastive Learning, Neural Information Processing Systems (NeurIPS), 2022 查看PDF
9. Zhao-Heng Yin, Weirui Ye, Qifeng Chen, Yang Gao, Planning for Sample Efficient Imitation Learning, Neural Information Processing Systems (NeurIPS), 2022 查看PDF
8. Weirui Ye, Pieter Abbeel, Yang Gao, Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions, Neural Information Processing Systems (NeurIPS), 2022 查看PDF
7. Renhao Wang, Hang Zhao, Yang Gao, CYBORGS: Contrastively Bootstrapping Object Representations by Grounding in Segmentation, European Conference on Computer Vision (ECCV), 2022 查看PDF
6. Yingdong Hu, Renhao Wang, Kaifeng Zhang, Yang Gao, Semantic-Aware Fine-Grained Correspondence, European Conference on Computer Vision (ECCV), 2022 查看PDF
5. Chia-Chi Chuang, Donglin Yang, Chuan Wen, Yang Gao, Resolving Copycat Problems in Visual Imitation Learning via Residual Action Prediction, European Conference on Computer Vision (ECCV), 2022 查看PDF
4. Chenyu Yang, Wanrong He, Yingqing Xu, and Yang Gao, EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer, European Conference on Computer Vision (ECCV), 2022 查看PDF
3. Chuan Wen*, Jierui Lin*, Jianing Qian, Yang Gao, Dinesh Jayaraman, Keyframe-Focused Visual Imitation Learning. International Conference on Machine Learning (ICML) , 2021 查看PDF
2. Weirui Ye, Shaohuai Liu, Thanard Kurutach, Pieter Abbeel, Yang Gao, Mastering Atari Games with Limited Data Advances, Neural Information Processing Systems (NeurIPS), 2021 查看PDF
1. Chuan Wen*, Jierui Lin*, Trevor Darrell, Dinesh Jayaraman, Yang Gao, Fighting Copycat Agents in Behavioral Cloning from Observation Histories, Neural Information Processing Systems (NeurIPS), 2020 查看PDF
