Short Bio

I am now an associate professor at the School of Artificial Intelligence, Nanjing 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 Technology, University 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 Computing, National 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.

[中文简历]

Research Interests

• Reinforcement learning, including deep reinforcement learning and multi-agent reinforcement learning
• Probabilistic planning, particularly in partially observable Markov decision processes
• Imitation learning based on generative adversarial nets

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.

Cong Fei, Bing Wang, Yuzheng Zhuang, Zongzhang Zhang, et al., Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets, Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-2020), pages 2929-2935, Yokohama, Japan, 2020.

Tianpei Yang, Jianye Hao, Zhaopeng Meng, Zongzhang Zhang, et al., Efficient Deep Reinforcement Learning via Adaptive Policy Transfer, Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI-2020), pages 3094-3100, Yokohama, Japan, 2020.

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.

刘全, 翟建伟, 章宗长, 钟珊, 周倩, 章鹏, 徐进. 深度强化学习综述. 计算机学报, 2018, 41(1): 1-27.

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.

章晓芳, 章宗长, 谢晓园, 周谊成. 一种基于优先级的迭代划分测试方法. 计算机学报, 2016, 39(11): 2307-2323.

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.

Aijun Bai, Feng Wu, Zongzhang Zhang, and Xiaoping Chen, Thompson Sampling based Monte-Carlo Planning in POMDPs, Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS-2014), pages 28-36, Portsmouth, USA, 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

• General Project, National Natural Science Foundation of China (NSFC), Deep Reinforcement Learning Based on Partially Observable Models: Theory and Applications, 2019.01-2022.12, Principal Investigator
• General Project, Natural Science Foundation at Jiangsu Province, Research on Theory and Methods of Planning and Reinforcement Learning in Partially Observable Environments, 2018.07-2021.06, Principal Investigator

Professional Services

• Senior Program Committee Member: IJCAI 2020-2021; AAAI 2019; ICAPS 2021; ECAI 2020
• Program Committee Member: AAAI 2018, 2020; ICML 2019-2021; IJCAI 2013, 2017-2019; NeurIPS 2018-2020; AAMAS 2021; ICLR 2021; ICAPS 2020; ECML-PKDD 2020; CoRL 2020; IJCNN 2020; CCDM 2020; ACML 2017-2019; PRICAI 2018-2019; ICA 2017-2019; ADPRL 2018; DAI 2019-2020; SSCI 2019; CCFAI 2019
• Young Associate Editor: Frontiers of Computer Science
• Journal Reviewer: Journal of Artificial Intelligence Research, IEEE Transactions on Cybernetics, ACM Transactions on Intelligent Systems and Technology, Machine Learning, Pattern Recognition, IEEE Computational Intelligence Magazine, Information Sciences, Frontiers of Computer Science, Neurocomputing, Knowledge-Based Systems, Applied Intelligence, 中国科学, 计算机学报, 软件学报, 自动化学报
• Workshop Co-chair: Asian Workshop on Reinforcement Learning (AWRL) 2016-2018, PRICAI 2018's Workshop on Methods and Applications of Reinforcement Learning
• Local Organizing Committee Chair: DAI 2020, MLA 2020

Teaching

• Multi-Agent Systems (for undergraduate students, Spring 2021) [textbook]
• Intelligent Systems: Design and Application (for undergraduate and graduate students, Spring 2020, 2021) [textbook]
• Control Theory and Methods (for undergraduate and graduate students, Fall 2020) [textbook]
• Reinforcement Learning (for graduate students, Fall 2020, with Prof. Yang Yu) [textbook]
• Intelligent Application Modeling (for undergraduate students, July 2019) [a summer course co-constructed with Tencent]
• Introduction to Software Engineering (for undergraduate students, 2015 - 2017)
• Computer Aided Software Engineering (for undergraduate students, 2014 - 2018)

Students

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:

• Feng Xu 徐峰 (2020.09 - , co-supervised with Prof. Ming Li)
• Weijian Liao 廖沩健 (2020.09 - , co-supervised with Prof. Ming Li)

Master Students:

• Yue Chen 陈越 (2019.09 - )
• Xianghan Kong 孔祥瀚 (2019.09 - )
• Tian Chang 常田 (2019.09 - )
• Guoyu Yang 杨国钰 (2020.09 - )
• Dongyu Guo 郭东宇 (2020.09 - )
• Di Xue 薛迪 (2020.09 - )
• Yafei Hu 胡亚飞 (2020.09 - )
• Quan He 贺泉 (2020.09 - )
• Chenyang Wu 吴晨阳 (2020.09 - )
• Zhaojin Wen 温昭晋 (2020.09 - )

Undergraduate Students:

• 2017.09 - (已推免): Tianchi Li 李天赐, Fuxiang Zhang 张福翔, Chenghe Wang 王铖鹤
• 2018.09 - : Rui Kong 孔锐, Fuguang Han 韩馥光, Wenjie Shen 沈雯杰, Feng Chen 陈烽, Chenxiao Gao 高辰潇, Aoran Wang 王傲然

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.

Mail:
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。

Zongzhang Zhang Ph.D., Associate Professor LAMDA Group School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University, P. R. China Office: Room A503, Yi Fu Building, Xianlin Campus Email: zzzhang@nju.edu.cn, zhangzongzhang@gmail.com