Email: yuf020ucsd.edu
Hi! I'm a master's student in Computer Science at UC San Diego, advised by Prof. Xiaolong Wang. I'm broadly interested in Robotics, Reinforcement Learning, and Computer Vision.
I received my Bachelar's degree with honors from the National Elite Program of Computer Science at Nanjing University, where I worked with Prof. Yang Yu in Leaning And Mining from DatA (LAMDA) Group. I was also fortunate to work with Prof. Kenneth Salisbury at Stanford Artificial Intelligence Lab (SAIL), Prof. Lin Shao and Prof. Xiangyu Yue.
Research
My research goal is to endow embodied agents with versatile skills by learning efficiently and continually in the physical world. Toward that end, my research is focused on data-driven and model-based decision-making, especially the following directions:
- World models/Model-based reinforcement learning for sample-efficient learning,
- Hierarchical learning/planning/control for solving long-horizon tasks, and
- Grounding foundation models(LLMs/VLMs) to handle complex robotic tasks.
Publications
Yunhai Feng*, Nicklas Hansen*, Ziyan Xiong*, Chandramouli Rajagopalan, Xiaolong Wang
Proceedings of the 7th Conference on Robot Learning (CoRL), November 2023 Oral presentation
@inproceedings{feng2023finetuning, title={Finetuning Offline World Models in the Real World}, author={Feng, Yunhai and Hansen, Nicklas and Xiong, Ziyan and Rajagopalan, Chandramouli and Wang, Xiaolong}, booktitle={Proceedings of the 7th Conference on Robot Learning (CoRL)}, year={2023} }
Jun Lv, Yunhai Feng, Cheng Zhang, Shuang Zhao, Lin Shao*, Cewu Lu*
Proceedings of Robotics: Science and Systems (RSS), July 2023 🏆 Best System Paper Award Finalist
@inproceedings{lv2023sam, title={SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering}, author={Lv, Jun and Feng, Yunhai and Zhang, Cheng and Zhao, Shuang and Shao, Lin and Lu, Cewu}, booktitle={Proceedings of Robotics: Science and Systems (RSS)}, year={2023} }
Ya Jing*, Xuelin Zhu*, Xingbin Liu*, Qie Sima, Taozheng Yang, Yunhai Feng, Tao Kong
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2023 CoRL 2022 Workshop on Pre-training for Robot Learning, December 2022
@inproceedings{jing2023explore author={Ya Jing, Xuelin Zhu, Xingbin Liu, Qie Sima, Taozheng Yang, Yunhai Feng, Tao Kong}, title={Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods}, booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year={2023} }
Shenli Yuan, Lin Shao, Yunhai Feng, Jiatong Sun, Teng Xue, Connor Yako, Jeannette Bohg, Kenneth Salisbury
Projects
Teaching
- Teaching Assistant: Problem Solving (IV) (2022 Spring), Nanjing University
- Teaching Assistant: Problem Solving (III) (2021 Fall), Nanjing University
Service
- Conference reviewer: IROS 2023, ICRA 2024
- Journal reviewer: IEEE Robotics and Automation Letters (RA-L)
Awards
- Best System Paper Award Finalist, RSS 2023
- Graduate Excellence Award, 2022
- Special Scholarship for Fundamental Subjects, 2021
- People's Scholarship (first prize), 2021
- National Elite Program Scholarship (first prize), 2020
- National Elite Program Scholarship (specialty prize), 2019