I am currently a master student at Tsinghua Shenzhen International Graduate School, Tsinghua University, advised by Prof. Xueqian Wang (王学谦). During my master’s degree, I also worked as an intern at Tencent AI Lab, collaborating with Dr. Liu Liu (刘浏) and Dr. Peilin Zhao (赵沛霖). Prior to that, I completed my bachelor’s degree at School of Mechatronics and Engineering, Harbin Institute of Technology.
Recently I have been working as a research assistant at Prof. Lin Shao (邵林)’s Lab and I am going to pursue my PhD degree under his supervision at National University of Singapore.
💡 Research Interests: I am broadly interested in research on the generalization and adaptation of RL agents.
You are very welcome to contact me regarding my research through email. I typically respond within a few days.
🔥 News
- 2024.06 One paper “ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots” was accepted to IROS 2024 as oral presentation.
- 2024.03 I was offered the PGF with admissions to ISEP to pursue PhD at NUS.
- 2024.02 One paper “DFWLayer: Differentiable Frank-Wolfe Optimization Layer” was accepted to Tiny Papers @ ICLR 2024 as notable.
- 2024.01 One paper “Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages” was accepted to ICLR 2024. Congratulations to Guozheng!
- 2023.09 I started to work as a research assistant in Prof. Lin Shao’s Lab.
- 2023.06 One paper “Dynamics Adapted Imitation Learning” was accepted to TMLR.
📝 Publications
Papers sorted by recency. * denotes equal contribution.
Selected Publications
(Oral Presentation) ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots
Zhixuan Xu*, Chongkai Gao*, Zixuan Liu*, Gang Yang*, Chenrui Tie, Haozhuo Zheng, Haoyu Zhou, Weikun Peng, Debang Wang, Tianyi Chen, Zhouliang Yu, Lin Shao
International Conference on Intelligent Robots and Systems (IROS), 2024
Dynamics Adapted Imitation Learning
Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao
Transactions on Machine Learning Research (TMLR), 2023
Openreview | Code | Bibtex
Other Publications
ICLR 2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages, Guozheng Ma, Lu Li, Sen Zhang, Zixuan Liu, Zhen Wang, Yixin Chen, Li Shen, Xueqian Wang, Dacheng Tao, International Conference on Learning Representations (ICLR), 2024. OpenReview | Code | BibtexTiny Papers @ ICLR 2024(Notable) DFWLayer: Differentiable Frank-Wolfe Optimization Layer, Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao, Tiny Papers @ ICLR 2024. OpenReview | Code | BibtexTNNLSNN-Based Reinforcement Learning Optimal Control for Inequality-Constrained Nonlinear Discrete-Time Systems With Disturbances, Shu Li, Liang Ding, Miao Zheng, Zixuan Liu, Xinyu Li, Huaiguang Yang, Haibo Gao, Zongquan Deng, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023. IEEE | Bibtex
🎖 Honors and Awards
- President Graduate Fellowship, National University of Singapore, 2024
- Outstanding Research Scholarship, Tsinghua University, 2023
- Outstanding Graduates, Harbin Institue of Technology, 2021
- National Scholarship, Ministry of Education of the People’s Republic of China, 2019
- Provincial Merit Students, Heilongjiang Provincial Education Department, 2019
📖 Educations
- 2024.08 - Present, PhD, National University of Singapore, Singapore.
- 2021.09 - 2024.06, M.E., Tsinghua University, Beijing, China.
- 2016.09 - 2021.06, B.E., Harbin Institute of Technology, Harbin, Heilongjiang, China.
💻 Internships
- 2023.09 - 2024.03, LinS Lab @ NUS SoC, Singapore.
- 2022.01 - 2023.08, Tencent AI Lab, Shenzhen, Guangdong, China.
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