| 2024 | AAAI | Towards Safe Policy Learning under Partial Identifiability: A Causal Approach. | Shalmali Joshi, Junzhe Zhang, Elias Bareinboim |
| 2023 | ICML | "Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. | Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi |
| 2022 | AIES | Towards Robust Off-Policy Evaluation via Human Inputs. | Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez, Himabindu Lakkaraju |
| 2022 | AISTATS | Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis. | Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, Himabindu Lakkaraju |
| 2021 | CIKM | Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. | Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi |
| 2020 | AIES | When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning. | Melissa D. McCradden, Mjaye Mazwi, Shalmali Joshi, James A. Anderson |
| 2018 | SDM | Co-regularized Monotone Retargeting for Semi-supervised LeTOR. | Shalmali Joshi, Rajiv Khanna, Joydeep Ghosh |