| 2025 | AISTATS | Distributional Off-policy Evaluation with Bellman Residual Minimization. | Sungee Hong, Zhengling Qi, Raymond K. W. Wong |
| 2024 | AISTATS | Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. | Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi |
| 2024 | ICLR | A Policy Gradient Method for Confounded POMDPs. | Mao Hong, Zhengling Qi, Yanxun Xu |
| 2024 | ICML | Model-based Reinforcement Learning for Confounded POMDPs. | Mao Hong, Zhengling Qi, Yanxun Xu |
| 2024 | ICML | A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models. | Jiayi Wang, Zhengling Qi, Raymond K. W. Wong |
| 2023 | AISTATS | Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. | Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li |
| 2023 | ICML | PASTA: Pessimistic Assortment Optimization. | Juncheng Dong, Weibin Mo, Zhengling Qi, Cong Shi, Ethan X. Fang, Vahid Tarokh |
| 2023 | UAI | Pessimistic Model Selection for Offline Deep Reinforcement Learning. | Chao-Han Huck Yang, Zhengling Qi, Yifan Cui, Pin-Yu Chen |
| 2022 | ICML | On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation. | Xiaohong Chen, Zhengling Qi |