Advancing Social Science Through Innovative Methods
The Duke Social Science Research Institute (SSRI) is pleased to launch the SSRI Distinguished Methods Speaker Series, bringing internationally recognized scholars to Duke to share cutting-edge research and methodological advances shaping the future of the social sciences.
The series welcomes faculty, graduate students, postdoctoral scholars, researchers, and research professionals from Duke and neighboring institutions, creating opportunities to learn from leading scholars, exchange ideas, and build connections across the broader research community.
Featuring experts in causal inference, survey methodology, machine learning, artificial intelligence, political methodology, and experimental research, the series highlights innovative approaches that are transforming social science research.
Whether your work is in political science, public policy, psychology, sociology, economics, public health, education, or another discipline, the SSRI Distinguished Speaker Series offers opportunities to engage with influential researchers whose methods are shaping the future of interdisciplinary social science.
Who Should Attend and Why?
The series is open to faculty, graduate students, postdoctoral scholars, staff, and researchers from Duke University and neighboring colleges and universities, as well as members of the broader research community with interests in social science methodology, data science, and quantitative research.
- Learn cutting-edge research methods
- Connect with leading scholars
- Explore applications of AI and machine learning in social science
- Ask questions and discuss your own research
Fall 2026 Speakers
All sessions will be held in Gross Hall 270
September 17–18, 2026 (10:00-11:30 am)
Erin Hartman
Associate Professor of Political Science
University of California, Berkeley
Erin Hartman’s research bridges statistics and the social sciences, developing methods that help researchers answer complex causal questions while strengthening collaboration across disciplines. Her work focuses on causal inference, survey design and analysis, external validity of experiments, falsification testing, and survey weighting.
Her visit will include a hands-on workshop for researchers and graduate students, followed by a public lecture.
- Research Areas
- Causal inference
- Survey design and analysis
- External validity
- Survey weighting
- Experimental methods
Save the date: registration coming soon!
October 23, 2026 (time TBA)
Arthur Spirling
Class of 1987 Professor of Politics
Director, Center for Statistics and Machine Learning
Princeton University
Arthur Spirling is a leading scholar in political methodology and computational social science. His current research explores machine learning and large language models, alongside work in legislative behavior and comparative politics, particularly British political development.
Research Areas
- Machine learning
- Large language models (LLMs)
- Political methodology
- Legislative behavior
- Computational social science
Save the date: registration coming soon!
November 13, 2026 (time TBA)
Donald Green
J.W. Burgess Professor of Political Science
Columbia University
Donald Green is internationally recognized for pioneering experimental methods in political science. His research spans voting behavior, political campaigns, mass media, hate crime, and research methodology, with much of his recent work using field experiments to understand voter mobilization and persuasion.
Research Areas
- Field experiments
- Voting behavior
- Political campaigns
- Research methods
- Experimental design
Save the date: registration coming soon!