| 2024 | AAAI | Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples. | Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam, Jay Nandy, Aravindan Raghuveer |
| 2023 | CIKM | Non-Uniform Adversarial Perturbations for Discrete Tabular Datasets. | Jay Nandy, Jatin Chauhan, Rishi Saket, Aravindan Raghuveer |
| 2022 | CIKM | Domain-Agnostic Contrastive Representations for Learning from Label Proportions. | Jay Nandy, Rishi Saket, Prateek Jain, Jatin Chauhan, Balaraman Ravindran, Aravindan Raghuveer |
| 2022 | IGARSS | Compact Feature Representation for Unsupervised Ood Detection. | Sudipan Saha, Jakob Gawlikowski, Jay Nandy, Xiao Xiang Zhu |
| 2022 | KDD | Multi-Variate Time Series Forecasting on Variable Subsets. | Jatin Chauhan, Aravindan Raghuveer, Rishi Saket, Jay Nandy, Balaraman Ravindran |
| 2021 | ICIP | Distributional Shifts In Automated Diabetic Retinopathy Screening. | Jay Nandy, Wynne Hsu, Mong-Li Lee |
| 2020 | IJCNN | Approximate Manifold Defense Against Multiple Adversarial Perturbations. | Jay Nandy, Wynne Hsu, Mong-Li Lee |
| 2018 | ICIP | Normal Similarity Network for Generative Modelling. | Jay Nandy, Wynne Hsu, Mong-Li Lee |
| 2016 | ICTAI | An Incremental Feature Extraction Framework for Referable Diabetic Retinopathy Detection. | Jay Nandy, Wynne Hsu, Mong-Li Lee |