Causal Inference across Fields: Methods, Insights, and Applications aims to bridge cutting-edge research with real-world policy applications.
The Workshop is part of the DSI Causal Inference Emerging Data Science Emergent Data Science Program that aims to facilitate cross-disciplinary exchange, where applied researchers from different disciplines can present their research questions and methodological issues. In turn, data science and causality researchers explore new and existing methods while promoting their research agendas.
Join us to foster collaborative exploration, amplifying the impact of causal inference and data science research on real-world policy challenges.
| October 22, 2025 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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9:15-9:45 |
Registration
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9:45-10:00 |
Opening Remarks TBC |
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10:00-11:00 |
Talk title TBC Melissa Dell, Professor, Department of Economics, Harvard University |
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11:00-12:00 |
Assessing Counterfactual Fairness in Policing with Imperfect Proxies of Civilian Behavior Dean C. Knox, Assistant Professor of Operations, Information, and Decisions, Assistant Professor of Statistics and Data Science, The Wharton School, University of Pennsylvania |
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12:00-1:15 |
Networking and Lunch
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1:15-2:15 |
Program Evaluation with Remotely Sensed Outcomes Ashesh Rambachan, Assistant Professor, Department of Economics, Massachusetts Institute of Technology |
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2:15-2:30 |
Coffee Break |
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2:30-3:30 |
Talks from any local/students |
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3:30-4:30 |
Panel discussion |
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4:30-4:45 |
Closing remarks TBC |
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Melissa Dell, Professor
Andrew E. Furer Professor of Economics, Department of Economics, Harvard University
Professor Dell’s research focuses on economic growth and political economy. She has examined the factors leading to the persistence of poverty and prosperity in the long run, the effects of trade-induced job loss on crime, the impacts of U.S. foreign intervention, and the effects of weather on economic growth. She has developed deep learning powered methods for curating social science data at scale, released in the open-source package Layout Parser. This work supports many of her current projects, which rely on digitizing historical sources far too large for manual digitization. Professor Dell is a senior scholar at the Harvard Academy for Area and International Studies and a research associate at the National Bureau of Economic Research.
Ashesh Rambachan
Silverman (1968) Family Career Development Assistant Professor of Economics at MIT
Professor Rambachan’s research interests are primarily in econometrics with a focus on applications of machine learning, focusing on algorithmic tools that drive decision-making in the criminal justice system and consumer lending markets and developing algorithmic procedures for discovering new behavioral models. Rambachan also develops methods for determining causation using cross-sectional and dynamic data.
Dean knox
Assistant Professor, Operations, Information and Decisions, Assistant Professor of Statistics and Data Science, Wharton University of Pennsylvania
Professor Knox is a computational social scientist and an assistant professor at the Wharton School of the University of Pennsylvania (Operations, Information, and Decisions Department; Department of Statistics and Data Science). He develops statistical models and methods for complex social-science applications, including in public management and communication. He has advised the U.S. Department of Justice, the American Civil Liberties Union, and the NAACP Legal Defense Fund on civil-rights data analysis. Dean is the inaugural recipient of Science magazine’s NOMIS early career award for interdisciplinary research. His research has appeared in top general science and disciplinary flagship journals including Science, the Proceedings of the National Academy of Sciences, Nature Human Behavior, the Journal of the American Statistical Association, and the American Political Science Review.
