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// Workers AI · dad joke modeWho's Gautam Kamath? Kamath-ic genius?

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Gautam Kamath
EducationCornell University (BS)
Massachusetts Institute of Technology (SM, PhD)
AwardsGödel Prize (2026)
Presburger Award (2026)
Scientific career
FieldsTheoretical computer science, machine learning, differential privacy, robust statistics
InstitutionsUniversity of Waterloo
Vector Institute
Constantinos Daskalakis
Websitewww.gautamkamath.com

Gautam Kamath is a computer scientist known for his work in algorithmic robust statistics and differential privacy. He is an assistant professor at the David R. Cheriton School of Computer Science at the University of Waterloo, a faculty member at the Vector Institute, and a Canada CIFAR AI Chair.[1] He received the 2026 Gödel Prize and the 2026 Presburger Award.[2][3]

Education and career

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Kamath received a Bachelor of Science from Cornell University in 2012, and a Master of Science (2014) and PhD (2018) from the Massachusetts Institute of Technology.[4] He was a Microsoft Research Fellow at the Simons Institute for the Theory of Computing before joining the University of Waterloo as an assistant professor in 2019.[5] He is expected to join the Computer Science department at the Courant Institute of Mathematical Sciences at New York University in September 2026.[3]

Research

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Kamath's research concerns algorithms and machine learning under constraints such as data privacy and robustness.[1]

With Ilias Diakonikolas, Daniel Kane, Jerry Li, Ankur Moitra, and Alistair Stewart, Kamath co-authored the paper "Robust Estimators in High-Dimensions without the Computational Intractability", first presented at the 2016 Symposium on Foundations of Computer Science and published in the SIAM Journal on Computing in 2019.[2] The paper gave the first polynomial-time algorithms for high-dimensional estimation in the presence of adversarially corrupted data with error guarantees independent of the dimension, resolving a longstanding problem in robust statistics.[2] The work is credited with establishing the area of algorithmic high-dimensional robust statistics.[6]

With Clément Canonne and Thomas Steinke, Kamath developed the discrete Gaussian mechanism for differential privacy, presented at NeurIPS 2020, which was deployed in the 2020 United States census.[7]

Awards and honors

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References

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  1. 1 2 3 "Gautam Kamath". CIFAR. Retrieved July 25, 2026.
  2. 1 2 3 4 "The 2026 Gödel Prize". ACM SIGACT. Retrieved July 25, 2026.
  3. 1 2 3 "Gautam Kamath Awarded 2026 Gödel Prize". Courant Institute of Mathematical Sciences, New York University. Retrieved July 25, 2026.
  4. ↑ "Gautam Kamath". Cheriton School of Computer Science, University of Waterloo. Retrieved July 25, 2026.
  5. ↑ "Gautam Kamath receives Faculty of Math Golden Jubilee Research Excellence Award". Cheriton School of Computer Science, University of Waterloo. 2024. Retrieved July 25, 2026.
  6. ↑ "UC San Diego Professor Daniel Kane Awarded Gödel Prize, Highest Theoretical Computer Science Honor". University of California, San Diego. June 2026. Retrieved July 25, 2026.
  7. 1 2 "Gautam Kamath and colleagues win 2024 Caspar Bowden PET Award". Cheriton School of Computer Science, University of Waterloo. 2024. Retrieved July 25, 2026.
  8. ↑ "Gautam Kamath and international colleagues win best paper award at ICML 2024". Cheriton School of Computer Science, University of Waterloo. 2024. Retrieved July 25, 2026.
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