PeopleofSuperintelligence

Researcher

Zaid Harchaoui

Zaid Harchaoui is a statistician and machine learning researcher at the University of Washington whose work spans optimization, federated learning and the evaluation of machine-written text. After a doctorate at Telecom Paris, a 2009 postdoctoral fellowship in Carnegie Mellon's Robotics Institute and permanent researcher years at Inria from 2010 to 2015, he spent 2015 and 2016 as a visiting assistant professor at NYU's Courant Institute. He coauthored the 2015 Catalyst paper on accelerating first-order optimization and was one of the 59 authors of the 2019 federated learning survey; his 2021 paper MAUVE, written with Krishna Pillutla, Yejin Choi and others, won a NeurIPS Outstanding Paper Award. He became a full professor at Washington in 2022 and was elected to the International Statistical Institute in 2024. He is a professor in Statistics and the Allen School, a cofounder of the NSF AI institute IFML and acting director of IFDS.

Now at
University of Washington, Institute for Foundations of Data Science and IFML
Works
260
Citations
17,742
h-index
46
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2009–2015

    Carnegie Mellon and Inria

    His doctorate comes from Telecom Paris, for research performed at CNRS, the French National Institute for Fundamental Research. He is a postdoctoral fellow in the Robotics Institute of Carnegie Mellon University in 2009, then a permanent researcher on the LEAR team at Inria from 2010 to 2015.

  2. 2015

    A Universal Catalyst paper

    In 2015, he coauthors "A Universal Catalyst for First-Order Optimization" with Hongzhou Lin and Julien Mairal. The paper introduces a generic scheme for accelerating first-order optimization methods in the sense of Nesterov, and it applies to gradient descent, SAG, SAGA, SVRG and related algorithms.

  3. 2015–2016

    Visiting at NYU Courant

    From 2015 to 2016, he is a visiting assistant professor at the Courant Institute of Mathematical Sciences at New York University. He is on leave from Inria and works at the Courant Institute and NYU's Center for Data Science.

  4. 2019

    Federated learning survey

    In 2019, he is among the 59 authors of "Advances and Open Problems in Federated Learning", with Peter Kairouz, H. Brendan McMahan and others. The survey covers recent advances and open problems in training models across many clients while the data stays decentralized, and it appears in Foundations and Trends in Machine Learning.

  5. 2021

    MAUVE wins at NeurIPS

    In 2021, he coauthors MAUVE with Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck and Yejin Choi. The measure compares the distribution of a text generation model with the distribution of human-written text using divergence frontiers, and the paper receives a NeurIPS 2021 Outstanding Paper Award.

  6. 2022

    Promotion to full professor

    He is promoted to full professor in the University of Washington's Department of Statistics in September 2022, where he is core faculty, adjunct faculty in the Allen School and a Senior Data Science Fellow in the eScience Institute. He serves on the executive committee of the NSF-funded Institute for Foundations of Data Science, and the National Science Foundation funds his research on "Scaling Laws of Deep Learning".

  7. 2024

    ISI election and AI testing

    He is elected a member of the International Statistical Institute in 2024. In September 2024, he describes in the UW College of Arts & Sciences Perspectives newsletter his tests of generative AI models, which struggle with tasks that people find easy, such as multiplying numbers.

  8. As of October 2026

    Professor at the University of Washington

    He is a professor at the University of Washington in the Department of Statistics and the Allen School of Computer Science and Engineering, a principal investigator and cofounder of the NSF AI Institute IFML, and the acting director of IFDS. In Spring 2026, he is a visiting scientist in the Federated and Collaborative Learning program at the Simons Institute for the Theory of Computing.

Career

  1. Since 2022Institute for Foundations of Data ScienceExecutive committee member
  2. Since 2016University of WashingtonProfessor
  3. NowIFMLCo-founder and principal investigator
  4. 2026Simons Institute for the Theory of ComputingVisiting scientist
  5. 2015–2016Courant Institute of Mathematical SciencesVisiting assistant professor
  6. 2015–2016New York University
  7. 2010–2015InriaPermanent researcher
  8. 2010–2020Université Grenoble Alpes
  9. 2009Carnegie Mellon UniversityPostdoctoral fellow
  10. 2007–2010CNRS
  11. 2007–2010Institut Polytechnique de Paris

Education

  1. Télécom ParisDoctorate

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Zaid Harchaoui. 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 company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Washington. 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.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Washington. 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.
  4. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes University of Washington. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.

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 Zaid Harchaoui yet. Send us a free-licensed photo.

  1. Prof. Zaid Harchaoui - Bio sites.google.com. Checked 20 October 2026.
  2. Zaid Harchaoui | DeepAI deepai.org. Checked 20 October 2026.
  3. [1506.02186] A Universal Catalyst for First-Order Optimization arxiv.org. Checked 20 October 2026.
  4. Zaid Harchaoui - LEAR team, Inria lear.inrialpes.fr. Checked 20 October 2026.
  5. [1912.04977] Advances and Open Problems in Federated Learning arxiv.org. Checked 20 October 2026.
  6. Announcing the NeurIPS 2021 Award Recipients – NeurIPS Blog blog.neurips.cc. Checked 20 October 2026.
  7. NeurIPS 2021 Awards neurips.cc. Checked 20 October 2026.
  8. [2102.01454] MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers arxiv.org. Checked 20 October 2026.
  9. Statistics Faculty Promotion in 2022 | University of Washington Department of Statistics stat.uw.edu. Checked 20 October 2026.
  10. Zaid Harchaoui | University of Washington Department of Statistics stat.uw.edu. Checked 20 October 2026.
  11. A Statistician Weighs in on AI | UW College of Arts & Sciences artsci.washington.edu. Checked 20 October 2026.
  12. Zaid Harchaoui | Simons Institute for the Theory of Computing simons.berkeley.edu. Checked 20 October 2026.