Welcome!

Hello! I am an Assistant Professor of Political Science at Texas A&M University, with an interdisciplinary background in law, political science, and statistics.

I study how political messages are structured and spread among political elites, media, and the public, and apply computational methods to measure these processes at scale. My work draws on natural language processing, machine learning, and large language models to capture complex features of political communication, including semantic similarity, rhetorical cohesion, and issue framing. These tools help me understand how parties build a collective voice and when elites lead or follow public discourse, with broader implications for political representation and democratic responsiveness.

I am also passionate about improving the transparency and reliability of AI-based measurement in social science. My ongoing projects develop transparent, evidence-grounded approaches to content analysis using large language models and explore how model-generated explanations affect independent human judgment and measurement accuracy.