About me
I am currently a Ph.D. candidate in the Robotics, Perception & AI Lab in the Department of Electronic Engineering at The Chinese University of Hong Kong(CUHK), Hong Kong SAR, CHina, supervised by Prof. Max Q.-H. Meng. Before that, I received my B.Eng. degree in Automation from Harbin Institute of Techonology(HIT), Harbin, China, in 2020.
Research Interest
Robotics, Learning-based control, Reinforcement learning.
Preprints
- Wei Zhan, Liting Sun, Di Wang, Haojie Shi, Aubrey Clausse, Maximilian Naumann, Julius Kummerle, Hendrik Konigshof, Christoph Stiller, Arnaud de La Fortelle, Masayoshi Tomizuka(2019). INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps.
- Haojie Shi, Qingxu Zhu, Lei Han, Wanchao Chi, Tingguang Li, Max Q.-H. Meng(2023). Terrain-Aware Quadrupedal Locomotion via Reinforcement Learning.
- Haojie Shi∗, Tingguang Li∗, Qingxu Zhu, Jiapeng Sheng, Lei Han and Max Q.-H. Meng(2023). An Efficient Model-Based Approach on Learning Agile Motor Skills without Reinforcement. Submitted to ICRA2024.
Publications
$\dagger$ indicates equal contribution, $*$ indicates corresponding authors.
Haojie Shi $\dagger$, Bo Zhou $\dagger$, Hongsheng Zeng, Fan Wang*, Yueqiang Dong, Jiangyong Li, Kang Wang, Hao Tian, Max Q-H Meng*. Reinforcement learning with evolutionary trajectory generator: A general approach for quadrupedal locomotion. IEEE Robotics and Automation Letters with ICRA, 2022.
Haojie Shi, Max Q-H Meng*. Deep koopman operator with control for nonlinear systems. IEEE Robotics and Automation Letters with IROS, 2022.
Teaching Experience
- TA in Singals and Systems(ENGG2030) 2021-2022
Contact Info
- Email: h.shi@link.cuhk.edu.hk
- Address: Room 432, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong