| 2024 | ICPR | Fair Latent Representation Learning with Adaptive Reweighing. | Puspita Majumdar, Raghav Sharma, Rohit Bhattacharya, Balraj Prajesh |
| 2024 | UAI | Statistical and Causal Robustness for Causal Null Hypothesis Tests. | Junhui Yang, Rohit Bhattacharya, Youjin Lee, Ted Westling |
| 2023 | UAI | Causal inference with outcome-dependent missingness and self-censoring. | Jacob M. Chen, Daniel Malinsky, Rohit Bhattacharya |
| 2023 | UAI | On Testability and Goodness of Fit Tests in Missing Data Models. | Razieh Nabi, Rohit Bhattacharya |
| 2022 | UAI | On testability of the front-door model via Verma constraints. | Rohit Bhattacharya, Razieh Nabi |
| 2021 | AISTATS | Differentiable Causal Discovery Under Unmeasured Confounding. | Rohit Bhattacharya, Tushar Nagarajan, Daniel Malinsky, Ilya Shpitser |
| 2021 | UAI | Path dependent structural equation models. | Ranjani Srinivasan, Jaron J. R. Lee, Rohit Bhattacharya, Ilya Shpitser |
| 2020 | ICML | Full Law Identification in Graphical Models of Missing Data: Completeness Results. | Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser |
| 2019 | UAI | Causal Inference Under Interference And Network Uncertainty. | Rohit Bhattacharya, Daniel Malinsky, Ilya Shpitser |
| 2019 | UAI | Identification In Missing Data Models Represented By Directed Acyclic Graphs. | Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins |