Welcome! I am a 5th year PhD student in Information Science at the University of Michigan, advised by Yan Chen, Qiaozhu Mei, and Alain Cohn.

My research lies at the intersection of artificial intelligence, human behavior, and computational social science. I study how AI and digital platforms reshape information, human judgment, communication, and decision-making, using field and lab experiments, causal inference, and LLM-based measurement. My broader research interests also include autonomous AI agents for scientific reasoning and discovery, as well as AI alignment and the evaluation of model behavior.

My work has appeared in PNAS and ICLR. One line of my research uses large-scale experiments and computational methods to study how digital platforms and generative AI affect visibility, credibility, communication, and consequential human decisions. A second line develops and evaluates autonomous agents for scientific reasoning and discovery, including agents that operate in cellular automata and partial differential equation environments. A third line studies AI alignment and model behavior, with an emphasis on developing rigorous methods for measuring, evaluating, and steering increasingly capable AI systems.

I was a research intern at Microsoft Research in the Economics and Computation group in Summer 2026 and will join Together AI as a Frontier Agents Research Intern in Fall 2026. My work received the Best Poster Award at the AI for Social Science Research Methods Workshop at Yale University. My research has also been supported by the OpenAI Researcher Access Program, the Innovations Growth Lab Seed Grant, and the Robert B. Zajonc Scholars Fund.

News: I am currently seeking tenure-track faculty positions and research scientist positions at industry research labs, where I hope to pursue research across human-centered AI, autonomous agents for scientific discovery, and AI alignment.