| 2023 | IJCNN | Single-Lead to Multi-Lead Electrocardiogram Reconstruction Using a Modified Attention U-Net Framework. | Akshit Garg, Vijay Vignesh Venkataramani, U. Deva Priyakumar |
| 2023 | IJCNN | Self-Supervision and Weak Supervision for Accurate and Interpretable Chest X-Ray Classification Models. | Abhiroop Talasila, Akshaya Karthikeyan, Shanmukh Alle, Maitreya Maity, U. Deva Priyakumar |
| 2022 | ICDCIT | Modern AI/ML Methods for Healthcare: Opportunities and Challenges. | Akshit Garg, Vijay Vignesh Venkataramani, Akshaya Karthikeyan, U. Deva Priyakumar |
| 2021 | HiPC | A Model of Graph Transactional Coverage Patterns with Applications to Drug Discovery. | A. Srinivas Reddy, P. Krishna Reddy, Anirban Mondal, U. Deva Priyakumar |
| 2021 | MICCAI | Linear Prediction Residual for Efficient Diagnosis of Parkinson's Disease from Gait. | Shanmukh Alle, U. Deva Priyakumar |
| 2021 | SMC | IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification. | Likith Reddy, Vivek Talwar, Shanmukh Alle, Raju S. Bapi, U. Deva Priyakumar |
| 2020 | AAAI | Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules. | Yashaswi Pathak, Siddhartha Laghuvarapu, Sarvesh Mehta, U. Deva Priyakumar |