Gautam Kamath is an Assistant Professor at the Cheriton School of Computer Science at the University of Waterloo. He is also a Faculty Member at the Vector Institute and a Canada CIFAR AI Chair. At Waterloo, he is further affiliated with Waterloo.AI and the Cybersecurity and Privacy Institute. His research interests are in reliable and trustworthy statistics and machine learning, particularly considerations such as privacy and robustness. He is an editor-in-chief of Transactions on Machine Learning Research (TMLR). He completed his B.S. at Cornell University, and his M.S. and Ph.D. at MIT. He also spent a year as a Microsoft Research Fellow at the Simons Institute for the Theory of Computing at UC Berkeley.
Assistant Professor, David R. Cheriton School of Computer Science, University of Waterloo
Canada CIFAR Artificial Intelligence Chair
Research Interests
- Privacy
- Robustness
- Statistics and Machine Learning
Highlights
- University of Waterloo Faculty of Math Golden Jubilee Research Excellence Award
- Canada CIFAR AI Chair in 2023
- NSERC Discovery Accelerator Supplement
- Cornell University Computer Science Prize for Academic Excellence
Publications
The role of adaptive optimizers for honest private hyperparameter selection
2022
Robustness implies privacy in statistical estimation
2023
Exploring the limits of model-targeted indiscriminate data poisoning attacks
2023
Private gans, revisited
2023
Advancing differential privacy: Where we are now and future directions for real-world deployment
2024
Private distribution learning with public data: The view from sample compression
2023
Distribution learnability and robustness
2024
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors
2024
Not All Learnable Distribution Classes are Privately Learnable
2024
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent
2023
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
2023