My teaching unites quantitative research methods with substantive, theoretical social science. I firmly believe that teaching students how to seek knowledge means giving them the tools to think concretely and conceptually about the social world, and the skills to answer their questions in meaningful ways. I emphasize research design as a wholistic process, involving unity between concept, theory, and method. This means being open to many possible ways of asking and answering questions. In the classroom, I strive to create an equitable, democratic environment in which participation is open to all and students are respected as equals and colleagues. As an advisor, I aim to keep students focused on their core research goals, helping them to develop their ideas across disciplines and methodological approaches.

Current Course Offerings

  • Massive digital traces of human behavior and ubiquitous computation have both extended and altered classical social science inquiry. This course surveys successful social science applications of computational approaches to the representation of complex data, information visualization, and model construction and estimation . We will reexamine the scientific method in the social sciences in context of both theory development and testing, exploring how computation and digital data enables new answers to classic investigations, the posing of novel questions, and new ethical challenges and opportunities. Students will review fundamental research designs such as observational studies and experiments, statistical summaries, visualization of data, and how computational opportunities can enhance them. The focus of the course is on exploring the wide range of contemporary approaches to computational social science.

  • This course focuses on applying computational methods to conducting social scientific research and the development of a strong research proposal. Students will identify a research question of their own interest that involves a direct reference to social scientific theory, the use of data, and a significant computational component. The students will review existing literature, identify an appropriate data source and conduct exploratory analysis, or develop a method (e.g. survey, experiment) through which they plan on collecting data, and generate a complete and well-motivated research proposal. The course will include modules on theoretical and practical considerations, including topics such as epistemological questions about research design, conducting literature reviews, data visualization and interpretation, reproducible research, writing and rhetoric, as well as presenting work to an audience.

  • Social science problems often have so many details and moving parts that it can be difficult for researchers to gain traction without models. In this course, we explore agent-based modeling approaches to understand these social science problems including cooperation and the development of culture. Agent-based models enable us to build an understanding from the bottom up, starting with simple assumptions and analyzing how patterns emerge at a larger scale. Through the term, we’ll cover the fundamentals of modeling, including basic principles of model design, data extraction, and canonical examples like Conway’s Game of Life, Schelling’s segregation model, and Boids/flocking. The course is balanced between social science readings and applications and hands-on coding. It cumulates in a final project consisting of an agent-based model designed by students to apply to a social science phenomenon.