Hello! I'm a computational social scientist and an assistant professor in Operations, Information, and Decisions and Statistics and Data Science at the Wharton School of the University of Pennsylvania. I study topics ranging from policing to causal inference and machine learning. My work uses many forms of data previously thought to be too messy or unstructured to study, such as audiovisual data conveying human emotion.
I am an Andrew Carnegie Fellow and the inaugural recipient of Science's NOMIS early career award for interdisciplinary research. My research has appeared or is forthcoming in 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. It has been funded by the National Science Foundation, Arnold Ventures, Microsoft, and Facebook. It has also received the Gosnell Prize for excellence in political methodology, the John T. Williams dissertation prize, and the best poster award by the Society for Political Methodology.
Please visit policingresearch.org for work by my group, Research on Policing Reform and Accountability, co-founded with Jonathan Mummolo. I am also a faculty fellow at Analytics at Wharton and an affiliate of the Quattrone Center for the Fair Administration of Justice.
Taylor Damann, Dean Knox, and Christopher Lucas. Conditionally accepted. "A framework for studying causal effects of speech style: Application to U.S. presidential campaigns." Journal of the Royal Statistical Society: Series A.
DownloadBocar Ba, Haosen Ge, Jacob Kaplan, Dean Knox, Mayya Komisarchik, Gregory Lanzalotto, Rei Mariman, Jonathan Mummolo, Roman Rivera, and Michelle Torres. Forthcoming. "Political diversity in U.S. police agencies." American Journal of Political Science.
DownloadJustin Grimmer, Dean Knox, and Brandon Stewart. 2023. "Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding." Journal of Machine Learning Research.
DownloadGuilherme Duarte, Noam Finkelstein, Dean Knox, Jonathan Mummolo, and Ilya Shpitser. 2023. "An automated solution to causal inference in discrete settings." Journal of the American Statistical Association (Theory and Methods).
Download DemoAndrew Reece, Gus Cooney, Peter Bull, Christine Chung, Bryn Dawson, Casey Fitzpatrick, Tamara Glazer, Dean Knox, Alex Liebscher, and Sebastian Marin. 2023. "Advancing an interdisciplinary science of conversation: Insights from a large multimodal corpus of human speech." Science Advances (Research Article).
DownloadCourtney Hilton, Cody Moser, Mila Bertolo, Harry Lee-Rubin, Dorsa Amir, Constance Bainbridge, Jan Simson, Dean Knox, Luke Glowacki, Andrzej Galbarczyk, Grazyna Jasienska, Cody Ross, Mary Beth Neff, Alia Martin, Laura Cirelli, Sandra Trehub, Jinqi Song, Minju Kim, Adena Schachner, Tom Vardy, Quentin Atkinson, Jan Antfolk, Purnima Madhivanan, Anand Siddaiah, Caitlyn Placek, Gul Deniz Salali, Sarai Keestra, Manvir Singh, Scott Collins, John Patton, Camila Scaff, Jonathan Stieglitz, Cristina Moya, Rohan Sagar, Brian Wood, Max Krasnow, Samuel Mehr. 2022. "Acoustic regularities in infant-directed speech and song across cultures." Nature Human Behavior (Article).
DownloadFotini Christia, Elizabeth Dekeyser, and Dean Knox. 2022. "Evidence on the nature of sectarian animosity: The Shi‘a case." Nature Human Behavior (Article).
DownloadDean Knox, Christopher Lucas, and Wendy K. Tam Cho. 2022. "Testing causal theories with learned proxies." Annual Review of Political Science (Invited).
DownloadDean Knox. 2021. "Revealing racial bias: Causal inference can make sense of imperfect policing data." Science (Essay).
DownloadDean Knox and Christopher Lucas. 2021. "A dynamic model of speech for the social sciences." American Political Science Review (Manuscript).
DownloadBocar Ba, Dean Knox, Jonathan Mummolo, and Roman Rivera. 2021. "The role of officer race and gender in police-civilian interactions in Chicago." Science (Research Article).
DownloadDean Knox, Will Lowe, and Jonathan Mummolo. 2020. "Administrative records mask racially biased policing." American Political Science Review (Manuscript).
DownloadDean Knox and Jonathan Mummolo. 2020. "Toward a general causal framework for the study of racial bias in policing." Journal of Political Institutions and Political Economy (Invited).
DownloadFragile Families Challenge Team. 2020. "Measuring the predictability of life outcomes with a scientific mass collaboration." Proceedings of the National Academy of Sciences (Research Report).
DownloadDean Knox and Jonathan Mummolo. 2020. "Making inferences about racial disparities in police violence." Proceedings of the National Academy of Sciences (Letter).
DownloadSamuel Mehr, Manvir Singh, Dean Knox, Daniel Ketter, Daniel Pickens-Jones, Stephanie Atwood, Christopher Lucas, Nori Jacoby, Alena Egner, Erin Hopkins, Rhea Howard, Joshua Hartshorne, Mariela Jennings, Jan Simson, Constance Bainbridge, Steven Pinker, Timothy O'Donnell, Max Krasnow, and Luke Glowacki. 2019. "Universality and diversity in human song." Science (Research Article).
DownloadDean Knox, Teppei Yamamoto, Matthew Baum, and Adam Berinsky. 2019. "Design, identification, and sensitivity analysis for patient preference trials." Journal of the American Statistical Association (Applications and Case Studies).
DownloadDean Knox and Jonathan Mummolo. 2020. "A widely touted study found no evidence of racism in police shootings. It’s full of errors." Washington Post.
LinkDean Knox and Jonathan Mummolo. 2020. "It took us months to contest a flawed study on police bias. Here's why that's dangerous." Washington Post.
LinkNaijia Liu, Xinlan Emily Hu, Yasemin Savas, Matthew Baum, Adam Berinsky, Allison Chaney, Christopher Lucas, Rei Mariman, Justin de Benedictis-Kessner, Andrew Guess, Dean Knox, and Brandon Stewart. "Algorithmic recommendations have limited effects on polarization: A naturalistic experiment on YouTube." Revise & resubmit.
DownloadJustin Grimmer, Dean Knox, and Sean Westwood. "Assessing the Reliability of Probabilistic U.S. Presidential Election Forecasts May Take Decades."
DownloadWharton OIDD/STAT 4770/7770. Introduction to Data Science in Python.
Princeton POL 571. Probability Theory.
Princeton POL 574. Machine Learning.