| 2025 | ICLR | Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning. | Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas J. Spanos |
| 2025 | ICLR | Tractable Multi-Agent Reinforcement Learning through Behavioral Economics. | Eric Mazumdar, Kishan Panaganti, Laixi Shi |
| 2025 | ICML | Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning. | Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman |
| 2025 | ICML | Learning to Steer Learners in Games. | Yizhou Zhang, Yian Ma, Eric Mazumdar |
| 2024 | ICML | Model-Free Robust ϕ-Divergence Reinforcement Learning Using Both Offline and Online Data. | Kishan Panaganti, Adam Wierman, Eric Mazumdar |
| 2024 | ICML | Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty. | Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman |
| 2023 | ICML | Algorithmic Collective Action in Machine Learning. | Moritz Hardt, Eric Mazumdar, Celestine Mendler-Dnner, Tijana Zrnic |
| 2022 | AISTATS | Zeroth-Order Methods for Convex-Concave Min-max Problems: Applications to Decision-Dependent Risk Minimization. | Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry, Lillian J. Ratliff |
| 2020 | ICML | On Approximate Thompson Sampling with Langevin Algorithms. | Eric Mazumdar, Aldo Pacchiano, Yi-An Ma, Michael I. Jordan, Peter L. Bartlett |
| 2020 | ICRA | Feedback Linearization for Uncertain Systems via Reinforcement Learning. | Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar, Shreyas Arora, Valmik Prabhu, S. Shankar Sastry, Claire J. Tomlin |
| 2019 | UAI | Convergence Analysis of Gradient-Based Learning in Continuous Games. | Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, Samuel Burden |