| 2025 | AIES | VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation. | David Egea, Barproda Halder, Sanghamitra Dutta |
| 2025 | AISTATS | Quantifying Knowledge Distillation using Partial Information Decomposition. | Pasan Dissanayake, Faisal Hamman, Barproda Halder, Ilia Sucholutsky, Qiuyi Zhang, Sanghamitra Dutta |
| 2025 | ICML | Quantifying Prediction Consistency Under Fine-tuning Multiplicity in Tabular LLMs. | Faisal Hamman, Pasan Dissanayake, Saumitra Mishra, Freddy Lcu, Sanghamitra Dutta |
| 2025 | ISIT | Private Counterfactual Retrieval with Immutable Features. | Shreya Meel, Pasan Dissanayake, Mohamed W. Nomeir, Sanghamitra Dutta, Sennur Ulukus |
| 2024 | ICLR | Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition. | Faisal Hamman, Sanghamitra Dutta |
| 2024 | ISIT | A Unified View of Group Fairness Tradeoffs Using Partial Information Decomposition. | Faisal Hamman, Sanghamitra Dutta |
| 2023 | AIES | REFRESH: Responsible and Efficient Feature Reselection guided by SHAP values. | Shubham Sharma, Sanghamitra Dutta, Emanuele Albini, Freddy Lcu, Daniele Magazzeni, Manuela Veloso |
| 2023 | ICML | Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees. | Faisal Hamman, Erfaun Noorani, Saumitra Mishra, Daniele Magazzeni, Sanghamitra Dutta |
| 2023 | UAI | In- or out-of-distribution detection via dual divergence estimation. | Sahil Garg, Sanghamitra Dutta, Mina Dalirrooyfard, Anderson Schneider, Yuriy Nevmyvaka |
| 2022 | ICML | Robust Counterfactual Explanations for Tree-Based Ensembles. | Sanghamitra Dutta, Jason Long, Saumitra Mishra, Cecilia Tilli, Daniele Magazzeni |
| 2020 | AAAI | An Information-Theoretic Quantification of Discrimination with Exempt Features. | Sanghamitra Dutta, Praveen Venkatesh, Piotr Mardziel, Anupam Datta, Pulkit Grover |
| 2020 | ICML | Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing. | Sanghamitra Dutta, Dennis Wei, Hazar Yueksel, Pin-Yu Chen, Sijia Liu, Kush R. Varshney |
| 2020 | ISIT | How else can we define Information Flow in Neural Circuits? | Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover |
| 2019 | ISIT | How should we define Information Flow in Neural Circuits? | Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover |
| 2018 | AISTATS | Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD. | Sanghamitra Dutta, Gauri Joshi, Soumyadip Ghosh, Parijat Dube, Priya Nagpurkar |
| 2018 | ISIT | A Unified Coded Deep Neural Network Training Strategy based on Generalized PolyDot codes. | Sanghamitra Dutta, Ziqian Bai, Haewon Jeong, Tze Meng Low, Pulkit Grover |
| 2017 | ISIT | Coded convolution for parallel and distributed computing within a deadline. | Sanghamitra Dutta, Viveck R. Cadambe, Pulkit Grover |
| 2016 | ISIT | Adaptivity provably helps: Information-theoretic limits on l0 cost of non-adaptive sensing. | Sanghamitra Dutta, Pulkit Grover |