معرفی
Gautam Kamath is an Assistant Professor at the University of Waterloo's Cheriton School of Computer Science, a Faculty Member at the Vector Institute, and a Canada CIFAR AI Chair. He leads The Salon, a research group focused on statistics, algorithms, machine learning, and optimization. His work bridges theoretical foundations with practical applications in data privacy and robustness, contributing to both academic research and real-world deployments that impact millions of users.
Dr. Kamath earned his PhD and SM degrees in Electrical Engineering and Computer Science at MIT, where he was advised by Costis Daskalakis. Prior to MIT, he graduated from Cornell University in May 2012 with a degree in Computer Science and Electrical and Computer Engineering, where he worked with Bobby Kleinberg. His academic journey reflects a strong foundation in both theoretical computer science and practical applications.
His research focuses on developing solutions for trustworthy and reliable machine learning and statistics, with particular emphasis on data privacy and robustness. He addresses fundamental problems in these areas, revitalizing statistical toolkits for the modern data era where privacy preservation is paramount. His work spans theoretical foundations of differential privacy to practical applications that have been deployed at scale, including contributions to systems that protect the sensitive information of hundreds of millions of individuals.
Analysis of his recent publications reveals a strong trend toward addressing the interplay between privacy, robustness, and machine learning performance. His work increasingly examines practical deployment challenges while maintaining theoretical rigor, with growing emphasis on diffusion models, generative AI, and the legal implications of AI systems. There's a clear trajectory from foundational privacy theory toward addressing real-world implementation challenges across diverse application domains.
- Canada CIFAR AI Chair
- Ontario Early Researcher Award
- 2024 Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies
- STOC Best Student Presentation Award
- ICML 2024 Best Paper Award
- Microsoft Research Fellow at the Simons Institute for the Theory of Computing
Dr. Kamath actively mentors students, with notable successes including Valentio Iverson winning the Germain-Erdős Undergraduate Award and Chris Trevisan receiving the CRA Outstanding Undergraduate Researcher Award. His service to the research community is extensive, serving as Editor-in-Chief of TMLR, on the Executive Committee of the Learning Theory Alliance, and on steering committees for major conferences including ICML, COLT, and ALT. He has organized numerous workshops focused on privacy-preserving machine learning and differential privacy.
Through The Salon research group, Dr. Kamath fosters a collaborative environment where postdoctoral fellows, graduate students, and undergraduates work together on cutting-edge problems at the intersection of statistics, algorithms, machine learning, and optimization. The group maintains strong connections with industry partners and participates in major research initiatives, including the Vector Institute's privacy and security research efforts. Looking forward, Dr. Kamath will be moving to the Computer Science department at NYU's Courant Institute of Mathematical Sciences in September 2026, where he plans to expand his research program.
