My research explores how people respond to critical societal challenges and interact with institutions. By integrating insights from behavioral political economy and political psychology, I aim to uncover the mechanisms that shape behaviors, policy preferences, and beliefs. In particular, I focus on how trust—both among individuals and in institutions—and perceptions of fairness influence support for crisis mitigation policies.

My methodological approach integrates computational text analysis, advanced statistical models, economic games, survey experiments, and formal and agent-based modeling to model and examine behaviors, policy preferences, norms, emotions, and narratives. By analyzing large-scale unstructured textual datasets, survey responses, and behavioral choices from social media, rally speech, survey experiments, and economic games, I aim to uncover the underlying mechanisms that drive behavior and policy support.

I teach Computational Text Analysis for Social Sciences, which covers machine learning and natural language processing using both R and Python. You can find the course materials on my teaching page.

I am a postdoctoral researcher at the University of Pennsylvania in Philosophy, Politics, and Economics and the Center for Social Norms and Behavioral Dynamics . I received my Ph.D. from the department of Political Science at Stony Brook University in 2023.