Zongzhang Zhang @ NJU-AI

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Zongzhang Zhang

Chinese name

Ph.D., Associate Professor
School of Artificial Intelligence
State Key Laboratory for Novel Software Technology
Nanjing University, P. R. China

Office: International College Building A503, Xianlin Campus
Email: ,

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Short Bio

I am now an associate professor at the School of Artificial IntelligenceNanjing University. I am also a member of the LAMDA group. From July 2014 to June 2019, I worked as an associate professor at the School of Computer Science and Technology, Soochow University. I received my Ph.D. degree from the School of Computer Science and TechnologyUniversity of Science and Technology of China, advised by Prof. Xiaoping Chen, in 2012. I worked with Prof. Mykel J. Kochenderfer as a visiting scholar at the Stanford Intelligent Systems Laboratory (SISL) from September 2018 to March 2019 and worked as a research fellow at the School of ComputingNational University of Singapore, from November 2012 to June 2014, under Prof. David Hsu and Prof. Wee Sun Lee. Before that, I visited the Rutgers Laboratory for Real-Life Reinforcement Learning (RL3), directed by Prof. Michael L. Littman, as a research visiting student, from October 2010 to October 2011. I also briefly worked as a research engineer at the Noah's Ark Lab in the Huawei Company in 2012.


Research Interests

Selected Publications

林嘉豪, 章宗长, 姜冲, 郝建业. 基于生成对抗网络的模仿学习综述. 计算机学报, 2020, 43(2): 326-351.

Yan Zheng, Jianye Hao, Zongzhang Zhang, Zhaopeng Meng, and Xiaotian Hao, Efficient Multiagent Policy Optimization Based on Weighted Estimators in Stochastic Environments, Journal of Computer Science and Technology, 2020, 35(2): 268-280.

Xiaobai Ma, Katherine R. Driggs-Campbell, Zongzhang Zhang, and Mykel J. Kochenderfer, Monte-Carlo Tree Search for Policy Optimization, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-2019), pages 3116-3122, Macao, China, 2019.

Yan Zheng, Zhaopeng Meng, Jianye Hao, Zongzhang Zhang, Tianpei Yang, and Changjie Fan, A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents, Proceedings of the 32nd Conference on Neural Information Processing Systems (NeurIPS-2018), pages 960-970, Montreal, Canada, 2018.

Zongzhang Zhang, Zhiyuan Pan, and Mykel J. Kochenderfer, Weighted Double Q-learning, Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-2017), pages 3455-3461, Melbourne, Australia, 2017.

Zongzhang Zhang, Qiming Fu, Xiaofang Zhang, and Quan Liu, Reasoning and Predicting POMDP Planning Complexity via Covering Numbers, Frontiers of Computer Science, 2016, 10(4): 726-740.

Zongzhang Zhang, David Hsu, Wee Sun Lee, Zhan Wei Lim, and Aijun Bai, PLEASE: Palm Leaf Search for POMDPs with Large Observation Spaces, Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS-2015), pages 249-257, Jerusalem, Israel, 2015.

Zongzhang Zhang, David Hsu, and Wee Sun Lee, Covering Number for Efficient Heuristic-Based POMDP Planning, Proceedings of the 31st International Conference on Machine Learning (ICML-2014), pages 28-36, Beijing, China, 2014.

Zongzhang Zhang, Michael L. Littman, and Xiaoping Chen, Covering Number as a Complexity Measure for POMDP Planning and Learning, Proceedings of the 26th Conference on Artificial Intelligence (AAAI-2012), pages 1853-1859, Toronto, Ontario, Canada, 2012.

Zongzhang Zhang and Xiaoping Chen, FHHOP: A Factored Hybrid Heuristic Online Planning Algorithm for Large POMDPs, Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI-2012), pages 934-943, Catalina Island, CA, USA, 2012.

Full publication list >>>

Authorized patents >>>

Ongoing Research Projects

Professional Services



I am very happy to work with the following students. Unless otherwise stated, my students are co-supervised with Prof. Yang Yu.

Ph.D. Students:

Master Students:

Undergraduate Students:

I still have some master students at the Soochow University.

To prospective students:

I am looking for self-driven, diligent, adaptable and resourceful students to work on exciting research in machine learning, including topics of reinforcement learning, probabilistic planning, imitation learning, multi-agent learning, etc. If you are passionate about research, you are welcome to contact me.

National Key Laboratory for Novel Software Technology, Nanjing University, Xianlin Campus Mailbox 603, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China
(In Chinese:) 南京市栖霞区仙林大道163号,南京大学仙林校区603信箱,计算机软件新技术国家重点实验室,210023。
Created on September 11, 2019