PeopleofSuperintelligence

Researcher

Aukosh Jagannath

Aukosh Jagannath is a mathematician whose research connects probability and statistical physics with data science and machine learning. He completed a mathematics PhD at NYU with a 2016 thesis on mean-field spin glasses, became a Benjamin Pierce Fellow and NSF postdoctoral fellow at Harvard by 2018, and joined Waterloo in 2019. His high-dimensional stochastic gradient descent research earned a NeurIPS 2022 Outstanding Paper award; he later coauthored an ICML 2025 spotlight paper on unsupervised pre-training and an ICLR 2026 paper on adaptive step sizes. He holds the Canada Research Chair in Mathematical Foundations of Data Science for 2023–2028 and is an associate professor in Waterloo's Department of Statistics and Actuarial Science as of October 2026.

Timeline

  1. 2016

    A thesis on spin glasses

    He completes a mathematics PhD at NYU with the thesis Variational and Structural Methods in Mean Field Spin Glasses, dated May 2016.

  2. By 2018

    Harvard postdoctoral fellowships

    By 2018, he holds undergraduate and graduate degrees from NYU and is a Benjamin Pierce Fellow and NSF postdoctoral fellow at Harvard University. He works in probability at the interface of statistical physics, data science, combinatorics, and statistics.

  3. 2019

    Joining Waterloo

    He comes to Waterloo in 2019 and works across mathematical physics, mathematical data science, optimization, and high-dimensional statistics.

  4. 2022

    An award-winning SGD paper

    By 2022, he is an assistant professor in Statistics and Actuarial Science and Applied Mathematics at Waterloo. With Gérard Ben Arous and Reza Gheissari, he coauthors High-dimensional limit theorems for SGD: Effective dynamics and critical scaling, which studies high-dimensional scaling limits of stochastic gradient descent with a constant step size and wins a NeurIPS 2022 Outstanding Paper award.

  5. 2023–2028

    A data science research chair

    He holds the Canada Research Chair in Mathematical Foundations of Data Science for 2023–2028.

  6. 2025

    An ICML spotlight paper

    He coauthors Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models with T. Jones-McCormick and S. Sen; the paper is an ICML 2025 spotlight.

  7. 2026

    Adaptive SGD at ICLR

    With T. Jones-McCormick and V. Sarangian, he coauthors High-dimensional limit theorems for SGD: Momentum and adaptive step sizes at ICLR 2026.

  8. As of October 2026

    Associate professor at Waterloo

    As of October 2026, he is an associate professor in the University of Waterloo's Department of Statistics and Actuarial Science, with cross-appointments in the Department of Applied Mathematics and in the Cheriton School of Computer Science.

Career

  1. Since 2019University of WaterlooAssistant Professor, Canada Research Chair in Mathematical Foundations of Data Science
  2. Harvard UniversityBenjamin Pierce Fellow and NSF postdoctoral fellow

Education

  1. 2016New York UniversityUndergraduate degree

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Aukosh Jagannath. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Waterloo. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Waterloo. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Waterloo. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Aukosh Jagannath yet. Send us a free-licensed photo.

  1. Aukosh Jagannath aukosh.github.io. Checked 21 October 2026.
  2. Aukosh Jagannath | Math Innovation | University of Waterloo uwaterloo.ca. Checked 21 October 2026.
  3. Algorithmic thresholds for tensor principle component analysis – MIT Statistics and Data Science Center stat.mit.edu. Checked 21 October 2026.
  4. Aukosh Jagannath wins Outstanding Paper award at NeurIPS 2022 | Mathematics | University of Waterloo uwaterloo.ca. Checked 21 October 2026.
  5. Announcing the NeurIPS 2022 Awards – NeurIPS Blog blog.neurips.cc. Checked 21 October 2026.
  6. Research chairs | Mathematics | University of Waterloo uwaterloo.ca. Checked 21 October 2026.
  7. ai @ nyu - Events | ai @ NYU cims.nyu.edu. Checked 21 October 2026.