I am Messi H.J. Lee, a researcher in machine psychology — a field dedicated to understanding the behavior and reasoning of AI systems through a psychological lens. I earned my PhD in Computational and Data Sciences from Washington University in St. Louis in May 2025, co-advised by Calvin K. Lai and Jacob M. Montgomery.
My research asks not just what models do, but why they behave the way they do — using frameworks from social psychology to study how AI systems develop and display human-like biases. My earlier work examined homogeneity bias in large language models, quantifying LLMs' tendency to represent marginalized groups as more homogeneous than their dominant counterparts. More recently, I have been studying implicit bias-like patterns in reasoning models — specifically, their tendency to consume more reasoning tokens when processing association-incompatible information compared to association-compatible information.