Agentic AI for Social Science Research
Instructor: Yongjun Zhang, PhD
Dates: July 1 – July 5, 2026
Course Description
This five-day intensive workshop introduces social scientists to a new paradigm of empirical research centered on collaboration with AI agents. As large language models become more capable, the key skill in research is shifting from coding expertise to the ability to formulate precise, meaningful questions. Participants will gain foundational understanding of how LLMs work and develop hands-on experience using AI tools to collect and clean data, conduct qualitative analysis, and synthesize findings.
The course emphasizes “Vibe Researching,” a natural language–driven approach to directing AI systems such as Claude Code, alongside Scholar-Skill, a framework that embeds methodological rigor and disciplinary knowledge into AI-assisted workflows. By the end of the workshop, participants will have built a customizable research pipeline, developed strategies for critically evaluating AI outputs, and gained clarity on how to integrate AI into their research while preserving the central role of human judgment.
About the Instructor
Yongjun Zhang is an Assistant Professor of Sociology and Institute for Advanced Computational Science at the State University of New York (Stony Brook). He is also a research affiliate at New York University. Dr. Zhang is a computational sociologist who combines computational, network, and statistical methods with large-scale datasets to study organizational, social, and political behavior, particularly focusing on segregation and polarization in different settings. Currently, he is using relational data from SafeGraph and Facebook as well as 190 million L2 voter records and 260 million Infutor consumer records to assess the antecedents and consequences of racial/partisan/income segregation in the United States. He is also using deep learning methods to detect and monitor anti-AAPI hate speech on Twitter since the COVID-19 outbreak. His research has been funded by OVPR and IACS seed grants at Stony Brook University. His work has appeared in leading social science journals such as the American Journal of Sociology, Demography, Journal of Marriage and Family, and Plos One, among others. He has won the 2020 James Coleman Award from the Sociology of Education Section at American Sociological Association and the 2021 SIM Best Paper Submission at the Academy of Management.