Hi! I’m Muni, a Fellow in Artificial Intelligence at Université PSL (Paris Sciences & Letters). I am affiliated with the LAMSADE research center at Université Paris Dauphine-PSL. I work closely with the MILES team members at LAMSADE. My current research interests are in trustworthy machine learning — specifically, robustness, privacy and fairness in machine learning.

I did my PhD in ECE at UW-Madison, advised by Prof. Varun Jog. My thesis was on the theoretical foundations of adversarial robustness in machine learning. Specifically, I explored the surprising connnections between adversarial robustness and optimal transport theory.

Previously, I have worked with Prof. Ambedkar Dukkipati in the Statistics and Machine Learning Group at IISc Bangalore. Before that, I was a software engineer at Samsung R&D Institute in Bangalore. I did my undergrad in Electrical Engineering at IIT Madras.

You can find my CV here.

Papers

1. Ilana Sebag, Muni Sreenivas Pydi, Jean-Yves Franceschi, Alain Rakotomamonjy, Mike Gartrell, Jamal Atif, Alexandre Allauzen. “Differentially Private Gradient Flow based on the Sliced Wasserstein Distance for Non-Parametric Generative Modeling” (under submission) 2024.
2. Alexandre Vérine, Muni Sreenivas Pydi, Benjamin Negrevergne, Yann Chevaleyre. “Optimal Budgeted Rejection Sampling for Generative Models.” AISTATS 2024.
3. Muni Sreenivas Pydi and Varun Jog. “The Many Faces of Adversarial Risk: An Expanded Study.” IEEE Transactions on Information Theory, 2023.
4. Alexandre Vérine, Benjamin Negrevergne, Muni Sreenivas Pydi and Yann Chevaleyre. “Precision-Recall Divergence Optimization for Generative Modeling with GANs and Normalizing Flows.” Neurips, 2023.
5. Eirini Ioannou, Muni Sreenivas Pydi and Po-Ling Loh, “Robust empirical risk minimization via Newton’s method”, Econometrics and Statistics, 2023.
6. Lucas Gnecco-Heredia, Muni Sreenivas Pydi, Yann Chevaleyre, Benjamin Negrevergne and Laurent Meunier. “On the Role of Randomization in Adversarially Robust Classification.” Neurips, 2023.
7. Muni Sreenivas Pydi and Varun Jog. “The Many Faces of Adversarial Risk.” Conference on Neural Information Processing Systems (NeurIPS), 2021.
8. Muni Sreenivas Pydi and Varun Jog. “Adversarial Risk via Optimal Transport and Optimal Couplings.” IEEE Transactions on Information Theory, 2021.
9. Muni Sreenivas Pydi and Varun Jog. “Adversarial Risk via Optimal Transport and Optimal Couplings.” International Conference on Machine Learning (ICML), 2020.
10. Muni Sreenivas Pydi, and Vishnu Suresh Lokhande. “Active Learning with Importance Sampling.” NeurIPS Workshop on ML with Guarantees, 2019.
11. Muni Sreenivas Pydi, Varun Jog, and Po-Ling Loh. “Graph-Based Ascent Algorithms for Function Maximization.” Communication, Control, and Computing (Allerton), 2018 56th Annual Allerton Conference on. IEEE, 2018.
12. Muni Sreenivas Pydi, and Ambedkar Dukkipati. “On Consistency of Compressive Spectral Clustering.” 2018 IEEE International Symposium on Information Theory (ISIT). IEEE, 2018.
13. Nagasubramanian, Karthik, and Muni Sreenivas Pydi. “Random access retransmission scheme for power limited nodes.” Communications (NCC), 2017 Twenty-third National Conference on. IEEE, 2017.
14. Guha, Ashwin, Muni Sreenivas Pydi, Biswajit Paria, and Ambedkar Dukkipati. “Analytic Connectivity in General Hypergraphs.” arXiv preprint arXiv:1701.04548 (2017).