The Center for Social Science Scholarship is pleased to continue our workshop series on generative AI, LLMs, and computational social science methods.
This series began with the basics of computing in R and how to use generative AI/LLMs in social science research workflows. Each session will be focused on getting faculty and students comfortable with deploying AI and generative AI models in their research, but with a deeper understanding of the ethical, equity, and environmental consequences of these models.
This series, which is supported through the Elkins Professorship, features several new speakers this spring. You can learn more about Dr. Eric Stokan’s award here. Meet our Graduate Assistant, Krishna Mummadi.
Spring 2026 Workshops
February 20 | 12-1:30pm | PUP 438
Social Network Analysis: Building Web-Based Applications for Experiential Learning
Led by: Dr. Steve McDonald,
Alumni Association Distinguished Graduate Professor of Sociology
University Faculty Scholar
Department of Sociology and Anthropology
North Carolina State University
February 27 | 12- 1:30pm | PUP 438
A City in Motion: How Everyday Routines Channel and Control Crime in Baltimore
Led by: Dr. Brian Soller, Associate Professor of Sociology (SAPH), UMBC
Brian Soller is an Associate Professor of Sociology at UMBC. He earned his PhD in Sociology from The Ohio State University in 2013. A specialist in quantitative methodology, Brian teaches courses in social statistics, sociological theory, and criminology. Brian’s research focuses on the intersections between urban sociology and social network analysis, specifically focusing on how to integrate methods and insights from these areas to understand variation in health and crime. His work has been published in leading academic journals, including the American Journal of Sociology (AJS), the American Sociological Review (ASR), Social Science & Medicine (SSM), the Journal of Health and Social Behavior (JHSB), and the American Journal of Community Psychology. His current research centers on the impact of routine mobility on crime, health, and aging and utilizes high-resolution digital mobility data to redefine how we understand spatial processes in the digital era.
Spatial clustering in crime is often treated as a statistical nuisance—modeled as spatial autocorrelation rather than explained. This talk reframes spatial dependence as a social process largely generated by routine human mobility. Integrating methods and insights from sociology, geography, and social network analysis, I use high-resolution GPS location data from a large panel of Baltimore-area residents to construct street-level mobility networks that capture patterns of street use by locals and non-locals, as well as network ties between street blocks formed through shared movement pathways. I show how these mobility-based connections help explain both crime concentration within blocks and spillover effects across connected blocks. No prior knowledge of R or advanced programming is required; rather than focusing on technical mechanics, the talk emphasizes how integrating theory and methods across traditionally siloed fields allows computational social science to identify the social processes that generate spatial patterns.
April 10 | 12-1:30pm | PUP 438
Geospatial Analysis
Led by: Krishna Mummadi, CS3 Graduate Assistant & GES Graduate Student
April 14 | 2-4pm | Walker Avenue, Suite 130 (Hybrid)
Foundations of Large Language Models
Led by: Dr. Josephine Namayanja, Executive Director, iHARP, UMBC
Rhoda Nankabirwa, iHARP Research Assistant and PhD Student, UMBC
April 22 | 12-1:30pm | Webex
Equity in Algorithms
Led by: Dr. Kayla Schwoerer
Assistant Professor of Public Administration, Vrije Universiteit, Amsterdam
April 29 | 12-1:30pm | Webex
Evaluating LLMs for Credible and Rigorous Social Science Research
Led by: Dr. Michael Overton, Associate Professor of Political Science and Public Administration, University of Idaho
ML Models for Causal Inference Analysis + HPC
Roy Prouty, Assistant Director for Research Computing, DoIT; UMBC Ph.D. Candidate, Computer Science, CSEE
Sai Vikas Amaraneni, iHARP Research Assistant and UMBC Ph.D. Student
Fall 2025 workshops
CS3 sponsored events are open for full participation by all individuals regardless of race, color, religion, sex, national origin, or any other protected category under applicable federal law, state law, and the University’s nondiscrimination policy.