People

Principal supervisor

Xin Li. Xin is currently an Associate Professor in the School of Computer Science at Beijing Institute of Technology, China. She received the B.Sc. and M.Sc. degrees in Computer Science from Jilin University China, and the Ph.D. degree in Computer Science at Hong Kong Baptist University. Her research focuses on the development of algorithms for (deep) reinforcement learning, network representation learning, with application to Single/Multi-player Games, Robotics, Network Alignment and Recommender Systems. [Website]

Ph.D. students

Yujie Fang. Yujie Fang is a Ph.D. student. She received her Bachelor’s degree in Computer Science from the Beijing Institute of Technology. From 2023 to 2024, she was a visiting student at A*STAR in Singapore. Her research interests include the optimization of graph task inference and the use of large language models for graph-related problems (LLM4Graph).


Min Wang. Min is a forth-year Ph.D. student in Computer Science at Beijing Institute of Technology. She received her M.Sc. degree from China Ship Research and Development Academy. She focuses on domain knowledge guided reinforcement learning and evolutionary game theory. Her work aims to improve the RL algorithms' sampling efficiency and speed up the agent's learning process. She is also interested in model-based planning and goal-conditioned RL.


Qianyu Chen. Qianyu is a third-year Ph.D. student in Computer Science and Technology at Beijing Institute of Technology. She focuses on EHR-based machine learning, including drug recommendation and health risk prediction. Her work aims to improve the accuracy and safety of recommendations and predictions in the medical field. She is also interested in graph learning.


Ruobing Wang. PhD student in Computer Science, Class of 2024, Beijing Institute of Technology, specializing in combinatorial optimization.


Yao-Hui Li. Yao-Hui Li is a second-year Ph.D. student in Computer Science at Beijing Institute of Technology. His research interests lie in model-based reinforcement learning, deep reinforcement learning, and offline reinforcement learning. He is also keen on exploring topics at the intersection of vision-language-action models and sim-to-real reinforcement learning.


Yangchuan Wang. Yangchuan Wang. A Ph.D. student in Computer Science at Beijing Institute of Technology, focusing on Reinforcement Learning (RL) and the alignment of Large Language Models (LLM).



Hongyu Zang. Former Ph.D. student in Computer Science at Beijing Institute of Technology, now working at Meituan. He received his B.Sc. degree in Computer Science from Beijing Forestry University. Hongyu's research focuses on Reinforcement Learning combining with Bayesian modeling, approximate inference and information bottleneck. His work aims to develop statistical models for analysing the reliability of Reinforcement Learning algorithms and use the information theory to explain the performance of RL algorithms.


M.S. and undergraduate students

Shuqi Yang. Shuqi is a second-year M.S. student at the School of Computer Science, Beijing Institute of Technology. He received his Bachelor's degree in Computer Science and Technology at Zhengzhou University. His research focuses on partially observable deep reinforcement learning.


Haojie Lei. Haojie is a first-year M.S. student at the School of Computer Science, Beijing Institute of Technology. He received his B.Sc. degree in Jilin University. Lei's research interest includes representation learning within DRL methods, the theoretical performance bounds of DRL methods and partially observable DRL.



Leiji Zhang. Leiji is currently an undergraduate student in Computer Science at Beijing Institute of Technology. His research interests include Deep Reinforcement Learning algorithms, Hierarchical Reinforcement Learning and applying Reinforcement Learning methods to autonomous driving systems.


Zhen Fang. Zhen Fang. Zhen is a first-year M.S. student at the School of Computer Science, Beijing Institute of Technology. He received his Bachelor's degree in Jinan University. His research interests include Deep Reinforcement Learning(DRL) algorithms and partially observable DRL.

Group alumni

  • Sen Chen. Former M.Sc. student, he focuses on partially observable reinforcement learning.
  • Jie Huang. Former M.Sc. student, now working at Baidu.
  • Li Zhang. Li's research interest includes model-free learning, model-based planning, their combination in both of reinforcement learning and imitation learning, partially observability, hierarchical DRL and multi-agent DRL. He is now working at Parametrix.ai.
  • Xinwen Wang. Xinwen worked on (deep) reinforcement learning under partially observable environment. He is now working at Microsoft(China).
  • Pengfei Zhu. Former M.Sc. student, now working at Alibaba.
  • Guanghui Miao. Former M.Sc. student, now working at Xiaohongshu.

    • Events

    Collaborators

    We are proud to have collaborative work with esteemed researchers in ML/RL fields.
  • William K. Cheung. Associate Vice-President, Professor in Department of Computer Science, Director of Centre for Health Informatics (HIC), Hong Kong Baptist University, Hong Kong, China. [Website]
  • Pascal Poupart. Professor & Canada CIFAR AI Chair at the Vector Institute Artificial Intelligence, Machine Learning, Health Informatics Waterloo AI Institute David R. Cheriton School of Computer Science University of Waterloo, Canada. [Website]
  • Ivor W. Tsang. ARC Future Fellow, Professor of Artificial Intelligence, University of Technology Sydney(UTS), Australia. [Website]
  • Mingzhong Wang. Lecturer in ICT （Faculty of Arts and Business)，University of the Sunshine Coast, Australia. [Website]

    • Our DRL group is also working with renowned company's AI group towards more real-world applications, e.g., 育碧 Ubisoft(China), 达闼 CloudMinds(Shenzhen).