I study how media shapes what we believe and how to make them work better for knowledge, democracy, and the public good.

My research explores how people navigate AI-driven and algorithmic media environments, where information overload, misinformation, and polarization pose significant challenges. I investigate how people self-select information within these complex environments and how media and personal factors shape beliefs, attitudes, and behaviors across science, health, and political communication.

As an interdisciplinary scholar with an engineering background, I combine computational data analysis with traditional quantitative methods, particularly surveys and experiments, and integrating digital trace data (e.g., clicks, viewing duration, and social endorsements) with self-reported measures. My goal is to develop evidence-based strategies that support informed, deliberative communication while countering adverse effects such as misinformation, polarization, and conspiracy theories.

My work has been published in peer-reviewed journals, including Human Communication Research, Information, Communication & Society, Journal of Health Psychology, among others.