About
I’m a Ph.D. student in Statistics at Harvard University and a Stone Ph.D. Scholar. Starting in Fall 2026, I’ll be joining the NYU Stern School of Business as an assistant professor of Technology, Operations, and Statistics.
My research develops statistical and computational methods to improve organizational decisions and public policy in areas like hiring, criminal justice, elections, and education. More broadly, I am interested in causal inference, applied statistics, computational social science, responsible AI, and the social impacts of technology.
Before coming to Harvard, I was a Ph.D. student in Computational and Mathematical Engineering at Stanford University and a Knight-Hennessy Scholar. I also spent two years as a data scientist at the Stanford Computational Policy Lab, working on projects with the public and private sector partners. I hold an A.B. in mathematics from Harvard, where I studied set theory and ergodic theory, and an M.Sc. in the history of science from the University of Oxford.
Publications
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Jongbin Jung, Sam Corbett-Davies, Johann D. Gaebler, Ravi Shroff, and Sharad Goel. “Measuring Disparate Impact in Human and Machine Decisions”. To appear in Proceedings of the National Academy of Sciences (2025).
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Johann D. Gaebler and Sharad Goel. “A Simple, Statistically Robust Test of Discrimination”. Proceedings of the National Academy of Sciences (2025). (EAAMO 2024 Best Paper Award.)
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Johann D. Gaebler, Sean J. Westwood, Shanto Iyengar, and Sharad Goel. “No News is Good News? The Declining Information Value of Broadcast News in America ”. PLOS ONE (2025).
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Johann D. Gaebler, Sharad Goel, Aziz Huq, and Prasanna Tambe. “Auditing large language models for race & gender disparities: Implications for artificial intelligence–based hiring ”. Behavioral Science & Policy (2025).
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Sam Corbett-Davies*, Johann D. Gaebler*, Hamed Nilforoshan*, Ravi Shroff, and Sharad Goel. “The Measure and Mismeasure of Fairness”. Journal of Machine Learning Research (2023).
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Johann D. Gaebler, Phoebe Barghouty, Sarah Vicol, Cheryl Phillips, and Sharad Goel. “Forgotten but not gone: A multi-state analysis of modern-day debt imprisonment”. PLOS ONE (2023).
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William Cai, Johann Gaebler, Justin Kaashoek, Lisa Pinals, Samuel Madden, and Sharad Goel. “Measuring Racial and Ethnic Disparities in Traffic Enforcement with Large-Scale Telematics Data”. PNAS: Nexus (2022).
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Johann D. Gaebler, William Cai, Guillaume Basse, Ravi Shroff, Sharad Goel, and Jennifer Hill. “A Causal Framework for Observational Studies of Discrimination”. Statistics and Public Policy (2022).
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Sabina Tomkins, Keniel Yao, Johann Gaebler, Tobias Konitzer, David Rothschild, Marc Meredith, and Sharad Goel. “Blocks as Geographic Discontinuities: The Effect of Polling-Place Assignment on Voting ”. Political Analysis (2022).
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Hamed Nilforoshan*, Johann Gaebler*, Ravi Shroff, and Sharad Goel. “Causal Conceptions of Fairness and Their Consequences”. International Conference on Machine Learning (2022). (ICML 2022 Outstanding Paper Award.)
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William Cai, Johann D. Gaebler, Nikhil Garg, and Sharad Goel. “Fair Allocation through Selective Information Acquisition”. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (2020).
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Johann Gaebler, Alexander Kastner, Cesar Silva, Xiaoyu Xu, and Zirui Zhou. “Partially Bounded Transformations have Trivial Centralizers”. Proceedings of the American Mathematical Society (2018).
Working Papers
- Guanting Chen, Johann D. Gaebler, Matt Peng, Chunlin Sun, and Yinyu Ye. “An Adaptive State Aggregation Algorithm for Markov Decision Processes”. Submitted, 2021.
(*: Denotes equal contribution.)