Wenhao Li 李文浩                                                                    

Assistant Professor

School of Software Engineering

Tongji University

Email: whli AT tongji DOT edu DOT cn

Office: 408R, Jishi Building, Jiading Campus, Tongji University

 

I am a Tenure-Track Assistant Processor in the School of Software Engineering at the Tongji University. My research interests mainly include theoretical understanding, algorithmic improvements and practical application of AI agents, reinforcement learning, multi-agent systems and generative models.

I focus on developing robust, efficient, and practical decision-making algorithms. I am also interested in the application of (multi-agent) reinforcement learning and generative models in practical problems like multi-agent pathfinding, embodied AI and computational social science.

Prior to that, I was a postdoctoral fellow at The Chinese University of Hong Kong, Shenzhen supervised by Prof. Hongyuan Zha. I received my Ph.D. from the School of Computer Science and Technology, East China Normal University in 2022, advised by Prof. Aimin Zhou and Prof. Hongyuan Zha. I received my B.E. from the School of Information Science and Engineering, Lanzhou University in 2016. During my Ph.D, I was a research intern in the Machine Learning Group at Tencent AI Lab advised by Dr. Dijun Luo. I was also a member of Tencent Rhion-Bird Talent Cultivation Program.

Please drop me an email if you are interested in collaborating with me.

Selected Awards

l Nomination Award for Excellent Doctoral Dissertation Award, by Shanghai Computer Society， 2023

l Excellent Graduate Award, by Shanghai Municipal Education Commission, 2022

l Outstanding Doctoral Thesis, by East China Normal University, 2022

n Thesis: Cooperation Promotion Multi-Agent Reinforcement Learning

l Tencent Rhion-Bird Talent Cultivation, 2020

l Excellent Graduate Award, by Lanzhou University, 2016

Selected Papers

Journals

[J4] Flexible Fully-Decentralized Approximate Actor-Critic for Cooperative Multi-Agent Reinforcement Learning. Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, Hongyuan Zha. Journal of Machine Learning Research, (JMLR, CCF-A), 24.178: 1-75, 2023, long paper (75 pages).

[J3] Structured Cooperative Reinforcement Learning with Time-varying Composite Action Space. Wenhao Li, Xiangfeng Wang, Bo Jin, Dijun Luo, Hongyuan Zha. IEEE Transactions on Pattern Analysis and Machine Intelligence, (TPMAI, CCF-A), 44.11: 8618-8634, 2022. IF: 24.314

[J2] Distributed and Parallel ADMM for Structured Nonconvex Optimization Problem. Xiangfeng Wang, Junchi Yan, Bo Jin, Wenhao Li. IEEE Transactions on Cybernetics, (TCYB, SCI-Q1), 51.9: 4540-4552, 2019. IF: 19.118

[J1] Learning Structured Communication for Multi-Agent Reinforcement Learning. Junjie Sheng, Xiangfeng Wang, Bo Jin, Junchi Yan, Wenhao Li, Tsung-Hui Chang, Jun Wang, Hongyuan Zha. Journal of Autonomous Agents and Multiagent Systems, (JAAMAS, CCF-B), 36.2: 50, 2022.

Conferences

[C13] Carbon Market Simulation with Adaptive Mechanism Design. Han Wang, Wenhao Li, Hongyuan Zha, Baoxiang Wang. International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2024.

[C12] Efficient Planning with Latent Diffusion. Wenhao Li. International Conference on Learning Representations (ICLR, TH-CPL-A), 2024.

[C11] Hierarchical Diffusion for Offline Decision Making. Wenhao Li, Xiangfeng Wang, Bo Jin, Hongyuan Zha. International Conference on Machine Learning (ICML, CCF-A), 2023.

[C10] Dealing with Non-Stationarity in Multi-Agent Reinforcement Learning via Trust Region Decomposition. Wenhao Li, Xiangfeng Wang, Bo Jin, Junjie Sheng, Hongyuan Zha. International Conference on Learning Representations (ICLR, TH-CPL-A), 2022.

[C9] Information Design in Multi-Agent Reinforcement Learning. Yue Lin, Wenhao Li, Hongyuan Zha, Baoxiang Wang. Neural Information Processing Systems (NeurIPS, CCF-A), 2023.

[C8] Iteratively-Refined Interactive 3D Medical Image Segmentation with Multi-Agent Reinforcement Learning. Xuan Liao, Wenhao Li, Qisen Xu, Xiangfeng Wang, Bo Jin, Xiaoyun Zhang, Yanfeng Wang, Ya Zhang. The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR, CCF-A), 2020.

[C7] VMAgent: Scheduling Simulator for Reinforcement Learning. Sheng, Junjie, Shengliang Cai, Haochuan Cui, Wenhao Li, Yun Hua, Bo Jin, Wenli Zhou et al. International Joint Conference on Artificial Intelligence (IJCAI, CCF-A), 2022.

[C6] HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem. Yun Hua, Xiangfeng Wang, Bo Jin, Wenhao Li, Junchi Yan, Xiaofeng He, Hongyuan Zha. International Conference on Knowledge Discovery and Data Mining (KDD, CCF-A), 2021.

[C5] Diverse Policy Optimization for Structured Action Space. Wenhao Li, Baoxiang Wang, Shanchao Yang and Hongyuan Zha. International Conference on Autonomous Agents and Multiagent Systems (AAMAS, CCF-B), Oral, 2023.

[C4] Model-Based Reinforcement Learning for Auto-Bidding in Display Advertising. Shuang Chen, Qisen Xu, Liang Zhang, Yongbo Jin, Wenhao Li and Linjian Mo. International Conference on Autonomous Agents and Multiagent Systems (AAMAS, CCF-B), Corresponding author, Oral, 2023.

[C3] Structured Diversification Emergence via Reinforced Organization Control and Hierachical

Consensus Learning. Wenhao Li, Xiangfeng Wang, Bo Jin, Junjie Sheng, Yun Hua, Hongyuan Zha.

International Conference on Autonomous Agents and Multiagent Systems (AAMAS, CCF-B), Oral, 2021.

[C2] Multi-Agent Path Finding with Prioritized Communication Learning. Wenhao Li*, Hongjun Chen*, Bo Jin, Wenzhe Tan, Hongyuan Zha and Xiangfeng Wang. International Conference on Robotics and Automation (ICRA, CCF-B), 2022.

[C1] Learning Optimal “Pigovian Tax” in Sequential Social Dilemmas. Yun Hua, Shang Gao, Wenhao Li, Bo Jin, Xiangfeng Wang and Hongyuan Zha. International Conference on Autonomous Agents and Multiagent Systems (AAMAS, CCF-B), Extended abstract, 2023.

Selected Grants

[P4] Reputation System based Multi-Agent Reinforcement Learning. Young Scientists Fund of the National Natural Science Foundation of China. Jan 2025 – Dec 2027. Principal inverstigator.

[P3] Policy Optimization for High-Dimensional Graph-Structured Action Space. China Postdoctoral Science Foundation. Nov 2022 – Jun 2024. Principal inverstigator.

[P2] Advanced Machine Learning for Structured Adaptive Self-evolution. The National Key Research and Development Program of China. 2021-2023. Participant.

[P1] Data Governance for Open Sharing of Multimodal Medical Data. Science and Technology Innovation Program of Shanghai. 2020-2022. Participant.

Professional Activities

l PC member/Reviewer:

n International Conference on Learning Representations (ICLR), 2022-2025

n Conference on Neural Information Processing Systems (NeurIPS), 2023

n International Conference on Machine Learning (ICML), 2024

n AAAI Conference on Artificial Intelligence (AAAI), 2025

n IEEE Transactions on Intelligent Vehicles (T-IV), 2023

n IEEE Transactions on Emerging Topics in Computational Intelligence (T-ETCI), 2023

Selected Talks

l Generative Models in Reinforcement Learning. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, Jun, 2023

l Structured Diversification Emergence via Reinforced Organization Control and Hierachical Consensus Learning. Third International Conference on Distributed Artificial Intelligence, October, 2021