About me

I am a Postdoctoral Researcher at the Social Resilience Lab at Aarhus University. My research lies at the intersection of political behavior, computational social science, and the scientific modeling of political information processing.

I study how people learn about politics, evaluate information sources, and form political beliefs in complex and changing information environments. A central focus of my research is how individual-level learning processes—such as credibility assessment, selective information acquisition, and social influence—interact with the structure of information environments to produce collective outcomes such as polarization, misinformation diffusion, and political resilience.

To explore these questions, I use a range of computational and empirical approaches, including agent-based modeling and simulation, randomized experiments, text-as-data, machine learning, and geospatial methods. My current research extends this agenda to adaptive and AI-mediated information environments, examining how interactions between users, information providers, and algorithmic systems shape political learning and belief formation.

I received my Ph.D. in Political Science from the University of Pittsburgh in 2024. My dissertation, Computational Models of Political Learning and Belief Polarization, developed computational models of how people learn about the credibility of political information sources and how these processes scale up through information choice and social networks. Before joining Aarhus University, I was a Postdoctoral Researcher on the ConsNet project at the University of Milano-Bicocca and BehaveLab at the University of Milan, where I conducted research on conspiracy beliefs, social networks, and political behavior.