I am an Assistant Professor of Computer Science at American University. My research is at the intersection of computational political science, AI, and digital studies. Specifically, I develop measurement methods for political science using AI/ML and NLP. These methods address research questions about topics such as political elite and non-elite ideology, affective polarization on social media, and hateful and abusive speech and memes. Recently, I have also been working on projects that examine competitive dynamics and antitrust issues in the AI industry.
Updates
- [April 2026] “Simulating Social Attitudes with LLMs: Accuracy, Demographic Effects, and Refusal Behavior in the Sensitive Domain of Suicide Prevention,” joint work with Cristina J. Perez, Michael P. Vasquez Jr., and Philippe Giabbanelli, was accepted to the NLP-CSS Workshop, co-located with ACL.
- [April 2026] “The Context Dependency of Demographic Bias in LLM Annotation,” joint work with Megan A. Brown, Shubham Atreja, and Libby Hemphill, and “Beyond Price: A Technical Quality Framework for AI Antitrust” were accepted to FAccT.
- [January 2026] “Beyond Price: A Technical Quality Framework for AI Antitrust” is now posted to SSRN.
- [December 2025] “Large Language Models Can Be a Viable Substitute for Expert Political Surveys When a Shock Disrupts Traditional Measurement Approaches” was accepted to the ACM Symposium on Applied Computing.
- [September 2025] “Emergent Racist Terminology Discovery,” joint work with Venkata Dhanush Kikkisetti, Suneela Maddineni, and Nathalie Japkowicz, was accepted to ICDM’s Demo Track.
Education
University of Michigan | PhD in Political Science and Scientific Computing, MA in Statistics
University of Chicago | BA in Political Science and Statistics