About
The Computational Social Science (CSS) Seminar Series hosts interdisciplinary scholars whose work lies at the intersection of data science and the social sciences, including statistics, economics, political science, public policy, and sociology. The seminar serves to highlight the recent work of researchers who are involved in both the development and the application of statistical methods to better understand social phenomena and processes. We welcome the participation of any and all members of the university who are interested in these interdisciplinary topics.
Hosted by:
- Christopher Harshaw, Assistant Professor of Statistics, Arts and Sciences, Columbia University
- Donald Green, Burgess Professor of Political Science, Arts and Sciences; and Chair of the DSI Computational Social Science Center, Columbia University
- Vardis Kandiros, Postdoctoral Fellow, DSI and Statistics Department, Columbia University
Upcoming Seminars: Fall 2026
CSS Seminar: Cyrus Samii, New York University
CSS Seminar: Amanda Kowalski, University of Michigan
Speaker Abstracts: 2026 - 2027 Academic Year
Event Date: October 29, 2026
Dylan Small, Professor of Statistics and Data Science, Co-Academic Director of the Dual Master's Degree in Statistics, Wharton School, University of Pennsylvania
Talk information coming soon!
Event Date: November 19, 2026
Cyrus Samii, is Professor in the Wilf Family Department of Politics of New York University. He writes and teaches on quantitative social science methodology, with an emphasis on causal inference. He is a prominent expert on the design of quantitative field research and social science randomized controlled trials. His applied research has focused on institutional innovation and strategies to address governance challenges in conflict-affected, emergency, and crisis contexts. He has carried out field studies in sites in Africa, Asia, and Latin America in collaboration with partners including the World Bank, United Nations, US Agency for International Development, UK Department for International Development, and Danish International Aid Agency, as well as government agencies, non-governmental organizations, and civil society organizations in the respective countries. From 2019-2023 he was Executive Director of the Evidence in Governance and Politics (EGAP) network. His work has appeared in peer-reviewed journals in political science, economics, and statistics. He received his PhD in political science from Columbia University, a master’s in international affairs from the Columbia University School of International and Public Affairs, and BA from Tufts University.
Talk information coming soon!
Event Date: December 10, 2026
Amanda Kowalski, the Gail Wilensky Professor of Applied Economics and Public Policy at the University of Michigan Department of Economics, is a health economist who specializes in bringing together experiments, models grounded in context-specific knowledge, and econometric techniques to answer questions that inform current debates in health policy.
Talk title: Counting Defiers: A Design-Based Model of an Experiment Can Reveal Evidence Beyond the Average Effect
Abstract: Using only a binary intervention and outcome and the design of the randomization within an experiment, we construct a design-based likelihood of the joint distribution of potential outcomes in the sample -- the numbers of always takers, compliers, defiers, and never takers. We develop a visualization to show that samples with defiers can sometimes generate the data in more ways than samples without, yielding a higher likelihood. This likelihood can vary within the Frechet bounds, even though the traditional likelihood does not. Evidence is weak, but it exists, as we illustrate with health applications and our dbmle package.