| 2025 | ASRU | Improving Streaming ASR via Differentially Private Fusion of Data from Multiple Sources. | Virat Shejwalkar, Om Thakkar, Steve Chien, Nicole Rafidi, Arun Narayanan |
| 2024 | Interspeech | Quantifying Unintended Memorization in BEST-RQ ASR Encoders. | Virat Shejwalkar, Om Thakkar, Arun Narayanan |
| 2023 | ICCV | The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning. | Virat Shejwalkar, Lingjuan Lyu, Amir Houmansadr |
| 2023 | SP | On the Pitfalls of Security Evaluation of Robust Federated Learning. | Momin Ahmad Khan, Virat Shejwalkar, Amir Houmansadr, Fatima M. Anwar |
| 2022 | SAC | Towards privacy aware deep learning for embedded systems. | Vasisht Duddu, Antoine Boutet, Virat Shejwalkar |
| 2022 | SP | Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning. | Virat Shejwalkar, Amir Houmansadr, Peter Kairouz, Daniel Ramage |
| 2022 | SENSYS | Security Analysis of SplitFed Learning. | Momin Ahmad Khan, Virat Shejwalkar, Amir Houmansadr, Fatima M. Anwar |
| 2021 | AAAI | Membership Privacy for Machine Learning Models Through Knowledge Transfer. | Virat Shejwalkar, Amir Houmansadr |
| 2021 | NDSS | Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning. | Virat Shejwalkar, Amir Houmansadr |
| 2020 | Mobiquitous | Quantifying Privacy Leakage in Graph Embedding. | Vasisht Duddu, Antoine Boutet, Virat Shejwalkar |
| 2019 | ACSAC | Revisiting utility metrics for location privacy-preserving mechanisms. | Virat Shejwalkar, Amir Houmansadr, Hossein Pishro-Nik, Dennis Goeckel |