About
I’m a Ph.D. student in Statistics at Harvard University and a Stone Ph.D. Scholar.
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.)