Professor Kong Lingkai is an Assistant Professor jointly appointed by the School of Computing and Data Science (host department) and the School of Public Health at the LKS Faculty of Medicine, The University of Hong Kong (HKU). Prior to joining HKU, he was a Postdoctoral Fellow at the Harvard John A. Paulson School of Engineering and Applied Sciences. He received his Ph.D. in Computational Science and Engineering from the Georgia Institute of Technology in the U.S.

His research focuses on building generative AI agents that can understand complex environments, reason effectively, and support decision-making in high-impact domains. He also works closely with public-sector partners in health and environmental sustainability to translate algorithmic innovations into real-world impact. His work has been published in leading AI and machine learning venues, including ICML, NeurIPS, and ICLR, and he has delivered tutorials at major data science conferences such as KDD. He is also a recipient of the Otto & Jenny Krauss Fellowship.

1. Lingkai Kong, Anagha Satish, Hezi Jiang, Akseli Kangaslahti, Andrew Ma, Wenbo Chen, Mingxiao Song, Lily Xu, and Milind Tambe. “Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions.” In International Conference on Machine Learning (ICML), 2026 (Spotlight)
2. Haichuan Wang, Tao Lin, Lingkai Kong, Ce Li, Hezi Jiang, and Milind Tambe. “Reward Shaping for Inference-Time Alignment: A Stackelberg Game Perspective.” In International Conference on Machine Learning (ICML), 2026
3. Akseli Kangaslahti, Davin Choo, Lingkai Kong, Milind Tambe, Alastair Heerden, and Cheryl Johnson. “Policy-Embedded Graph Expansion: Networked HIV Testing with Diffusion-Driven Network Samples.” In International Joint Conferences on Artificial Intelligence (IJCAI), 2026
4. Lingkai Kong, Haichuan Wang, Tonghan Wang, Guojun Xiong, and Milind Tambe. “Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data.” In Advances in Neural Information Processing Systems (NeurIPS), 2025 (Spotlight)
5. Shresth Verma, Alayna Nguyen, Niclas Boehmer, Lingkai Kong, and Milind Tambe. “PRIORITY2REWARD: Incorporating Healthworker Preferences for Resource Allocation Planning.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2025
6. Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, and Chao Zhang. “AdaPlanner: Adaptive Planning from Feedback with Language Models.” In Advances in Neural Information Processing Systems (NeurIPS), 2023
7. Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, and Chao Zhang. “End-to-End Stochastic Optimization with Energy-based Model.” In Advances in Neural Information Processing Systems (NeurIPS), 2022 (Oral)
8. Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, and B. Aditya Prakash. “When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting.” In Advances in Neural Information Processing Systems (NeurIPS), 2021