| 2026 | EACL | Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders. | Aaron J. Li, Suraj Srinivas, Usha Bhalla, Himabindu Lakkaraju |
| 2026 | SIGMOD | Demonstration of WayPoint: Interactive Natural Language Querying for Spatio-Temporal Video Events. | Taehyeok Jang, Jie Jeff Xu, Suraj Srinivas, Jorge Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong |
| 2025 | ICML | How Much Can We Forget about Data Contamination? | Sebastian Bordt, Suraj Srinivas, Valentyn Boreiko, Ulrike von Luxburg |
| 2024 | UAI | Characterizing Data Point Vulnerability as Average-Case Robustness. | Tessa Han, Suraj Srinivas, Himabindu Lakkaraju |
| 2023 | UAI | On Minimizing the Impact of Dataset Shifts on Actionable Explanations. | Anna P. Meyer, Dan Ley, Suraj Srinivas, Himabindu Lakkaraju |
| 2022 | CVPR | Cyclical Pruning for Sparse Neural Networks. | Suraj Srinivas, Andrey Kuzmin, Markus Nagel, Mart van Baalen, Andrii Skliar, Tijmen Blankevoort |
| 2021 | ICLR | Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability. | Suraj Srinivas, Franois Fleuret |
| 2018 | ICML | Knowledge Transfer with Jacobian Matching. | Suraj Srinivas, Franois Fleuret |
| 2017 | CVPR | Training Sparse Neural Networks. | Suraj Srinivas, Akshayvarun Subramanya, R. Venkatesh Babu |
| 2016 | BMVC | Learning Neural Network Architectures using Backpropagation. | Suraj Srinivas, Radhakrishnan Venkatesh Babu |
| 2015 | BMVC | Data-free Parameter Pruning for Deep Neural Networks. | Suraj Srinivas, R. Venkatesh Babu |
| 2014 | ICIP | Controlled blurring for improving image reconstruction quality in flutter-shutter acquisition. | Suraj Srinivas, Aniruddha Adiga, Chandra Sekhar Seelamantula |