Researcher

Susan Athey

Also known as Susan Carleton Athey

Susan Athey is a Stanford economist who develops machine learning methods to measure how interventions affect different people. She studied economics, mathematics, and computer science at Duke, completed a Stanford PhD in 1995, and taught at MIT, Stanford, and Harvard before returning to Stanford GSB in 2013. Her work includes causal trees with Guido Imbens, generalized random forests with Julie Tibshirani and Stefan Wager, and a 2025 study of wage disparities using foundation models. She received the 2007 John Bates Clark Medal, became the Golub Capital Social Impact Lab’s first faculty director in 2019, and served as the Justice Department’s chief antitrust economist from 2022 to 2024. As of October 2026, she is Stanford GSB’s Economics of Technology Professor and the lab’s founding director.

Works
488
Citations
32,722
h-index
71

Publication numbers from OpenAlex, as of 27 October 2026.

Timeline

  1. 1991–1995

    Duke and Stanford degrees

    She earns a BA in economics, mathematics, and computer science at Duke University in 1991 and a PhD at Stanford Graduate School of Business in 1995. Her doctoral advisors are Paul Milgrom, John Roberts, and Edward Lazear.

  2. 1995–2006

    MIT, Stanford, and Harvard

    In 1995, she becomes an assistant professor of economics at MIT. She joins Stanford in 2001, holds the Holbrook Working Professor of Economics chair, and moves to Harvard’s Faculty of Arts and Sciences as a professor of economics in July 2006.

  3. 2007–2012

    Clark Medal and academy elections

    She receives the John Bates Clark Medal in 2007. Election to the American Academy of Arts and Sciences follows in 2008, and she becomes a member of the National Academy of Sciences in 2012.

  4. 2013

    Professor at Stanford GSB

    In 2013, she returns to Stanford as a professor at the Graduate School of Business. Her chief economist role at Microsoft ends in 2013; work with Bing’s randomized experiments helps shape her interest in combining machine learning with methods for measuring causal effects.

  5. 2016

    Trees for causal effects

    With Guido W. Imbens, she publishes “Recursive Partitioning for Heterogeneous Causal Effects” in 2016. The method uses regression trees to find groups with different treatment effects, with separate samples used to form the groups and estimate their effects.

  6. 2019

    Generalized random forests

    In 2019, she publishes “Generalized Random Forests” with Julie Tibshirani and Stefan Wager in the Annals of Statistics. The work extends random forests to statistical tasks such as quantile regression and treatment-effect estimation, and provides methods for confidence intervals. Its software implementation, grf, is available for R and C++.

  7. 2019

    Golub Capital Social Impact Lab

    In 2019, she leads Stanford GSB’s new Golub Capital Social Impact Lab as its initial faculty director. The lab brings academics, staff, and students together to help social sector organizations test digital tools and measure their effects.

  8. 2022–2024

    Chief economist at Justice

    From 2022 to 2024, she takes leave from Stanford to serve as chief economist of the US Department of Justice Antitrust Division. She also serves as president of the American Economic Association in 2023.

  9. 2025

    HAI and foundation models

    In 2025, she serves as a senior fellow at the Stanford Institute for Human-Centered Artificial Intelligence. In May 2025, she publishes “Estimating Wage Disparities Using Foundation Models” with Keyon Vafa and David M. Blei. The paper develops methods to fine-tune foundation models for statistical estimation and uses career histories to study the gender wage gap.

  10. As of October 2026

    Professor and lab director

    As of October 2026, she is the Economics of Technology Professor at Stanford Graduate School of Business and founding director of its Golub Capital Social Impact Lab. Her lab uses machine learning to estimate how interventions affect different people, and applies bandit algorithms and reinforcement learning to personalize digital services.

Career

  1. Since 2019Stanford UniversityFounding Director of Golub Capital Social Impact Lab
  2. NowStanford UniversitySenior Fellow, Stanford Institute for Human-Centered Artificial Intelligence
  3. NowStanford UniversityEconomics of Technology Professor
  4. NowStanford UniversityProfessor of Economics by Courtesy
  5. 2022–2024United States Department of JusticeChief Economist
  6. 2018–2021Stanford Institute for Economic Policy Research
  7. From 2013Stanford UniversityProfessor
  8. 2008–2013MicrosoftConsulting Chief Economist
  9. 2006–2012Harvard UniversityProfessor of Economics
  10. 2004–2006Stanford UniversityHolbrook Working Professor of Economics
  11. 2002–2006Federal Reserve
  12. 2001–2003Stanford UniversityAssociate Professor of Economics
  13. Until 2001Massachusetts Institute of TechnologyCastle Krob Career Development Associate Professor of Economics
  14. 2001–2005University of California, Los Angeles
  15. 1999–2026National Bureau of Economic Research
  16. From 1995Massachusetts Institute of TechnologyAssistant Professor of Economics
  17. 1995–2003Colorado State University

Education

  1. 1995Stanford UniversityPhD in Economics
  2. 1991Duke UniversityBA in Economics, Mathematics, and Computer Science

Sources and credits

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  1. Susan Athey CV web.mit.edu. Checked 27 October 2026.
  2. Stanford’s Athey named FAS professor of economics news.harvard.edu. Checked 27 October 2026.
  3. Susan Athey gsb.stanford.edu. Checked 27 October 2026.
  4. Pioneering Tech Economist Susan Athey Joins Federal Antitrust Team gsb.stanford.edu. Checked 27 October 2026.
  5. Recursive Partitioning for Heterogeneous Causal Effects gsb.stanford.edu. Checked 27 October 2026.
  6. Generalized Random Forests: Journal Article gsb.stanford.edu. Checked 27 October 2026.
  7. Golub Capital Social Impact Lab Aims to Enhance Social Sector Effectiveness gsb.stanford.edu. Checked 27 October 2026.
  8. Stanford HAI Welcomes Six Distinguished Scholars as Senior Fellows hai.stanford.edu. Checked 27 October 2026.
  9. Estimating Wage Disparities Using Foundation Models: Journal Article gsb.stanford.edu. Checked 27 October 2026.
  10. AI & Machine Learning gsb.stanford.edu. Checked 27 October 2026.