| 2025 | ICML | "Who experiences large model decay and why?" A Hierarchical Framework for Diagnosing Heterogeneous Performance Drift. | Harvineet Singh, Fan Xia, Alexej Gossmann, Andrew Chuang, Julian C. Hong, Jean Feng |
| 2023 | AIES | Measures of Disparity and their Efficient Estimation. | Harvineet Singh, Rumi Chunara |
| 2023 | ICML | When do Minimax-fair Learning and Empirical Risk Minimization Coincide? | Harvineet Singh, Matthus Kleindessner, Volkan Cevher, Rumi Chunara, Chris Russell |
| 2023 | ICML | "Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. | Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi |
| 2022 | AIES | Fair, Robust, and Data-Efficient Machine Learning in Healthcare. | Harvineet Singh |
| 2022 | AIES | Towards Robust Off-Policy Evaluation via Human Inputs. | Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju |
| 2022 | CVPR | Segmenting across places: The need for fair transfer learning with satellite imagery. | Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara |
| 2022 | UAI | Data poisoning attacks on off-policy policy evaluation methods. | Elita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju |
| 2019 | UAI | Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank. | Gaurush Hiranandani, Harvineet Singh, Prakhar Gupta, Iftikhar Ahamath Burhanuddin, Zheng Wen, Branislav Kveton |
| 2018 | EDM | Modeling Hint-Taking Behavior and Knowledge State of Students with Multi-Task Learning. | Harvineet Singh, Shiv Kumar Saini, Ritwick Chaudhry, Pradeep Dogga |
| 2018 | WSDM | Modeling Time to Open of Emails with a Latent State for User Engagement Level. | Moumita Sinha, Vishwa Vinay, Harvineet Singh |