Scholar
Gautam Kamath
Google Scholar ID: MK6zHkYAAAAJ
Assistant Professor @ University of Waterloo, Faculty Member @ Vector Institute
Statistics
Machine Learning
Privacy
Robustness
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
5,314
H-index
36
i10-index
60
Publications
20
Co-authors
110
list available
Contact
CV
Open ↗
Twitter
Open ↗
GitHub
Open ↗
Publications
13 items
Rethinking Benchmarks for Differentially Private Image Classification
2026
Cited
1
Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
2025
Cited
0
Not All Samples Are Equal: Quantifying Instance-level Difficulty in Targeted Data Poisoning
2025
Cited
0
On the Learnability of Distribution Classes with Adaptive Adversaries
2025
Cited
0
Demystifying Foreground-Background Memorization in Diffusion Models
2025
Cited
0
Optimal Differentially Private Sampling of Unbounded Gaussians
2025
Cited
0
BridgePure: Revealing the Fragility of Black-box Data Protection
2024
Cited
0
The Broader Landscape of Robustness in Algorithmic Statistics
arXiv.org · 2024
Cited
3
Load more
Resume (English only)
Academic Achievements
- Multiple papers accepted to NeurIPS 2025, ICLR 2025, COLT 2025, etc.
- Recipient of the Ontario Early Researcher Award
- Published papers in various academic journals and conferences
- Served on program committees for multiple academic conferences
- Organized the Vector Institute ML Privacy and Security workshop
Research Experience
- Assistant Professor at the Cheriton School of Computer Science, University of Waterloo
- Faculty Member at the Vector Institute
- Canada CIFAR AI Chair
- Microsoft Research Fellow at the Simons Institute for the Theory of Computing, Fall 2018 and Spring 2019 semesters
- Will be joining the Computer Science department at the Courant Institute of Mathematical Sciences, NYU in September 2026
Education
- Ph.D., Massachusetts Institute of Technology (MIT), Advisor: Costis Daskalakis, Theory of Computing Group, CSAIL
- Bachelor's degree, Cornell University, Majors: Computer Science and Electrical and Computer Engineering, Advisor: Bobby Kleinberg
Background
- Reliable and trustworthy statistics and machine learning
- Considerations such as data privacy and robustness
Miscellany
- Personal interests include collecting anonymous feedback
- Runs The Salon research group
Co-authors
110 total
Jonathan Ullman
Associate Professor of Computer Science, Northeastern University
Jerry Li
University of Washington
Vikrant Singhal
Research Associate, Harvard University
Clément L. Canonne
University of Sydney
Constantinos Daskalakis
Professor of Computer Science, MIT
Daniel Kane
University of California, San Diego
Ilias Diakonikolas
University of Wisconsin-Madison
Co-author 8
×
Welcome back
Sign in to Agora
Welcome back! Please sign in to continue.
Email address
Password
Forgot password?
Continue
Do not have an account?
Sign up