Byunghwee Lee

Byunghwee Lee is a postdoctoral research associate at the University of Virginia School of Data Science, working in Professor Yong-Yeol Ahn’s lab. Lee's research focuses on human belief dynamics, computational social science, and cultural analytics. He combines theoretical frameworks from statistical physics with computational methods such as natural language processing, image analysis, and machine learning, leveraging high-performance computing resources.

Before joining UVA in August 2025, Lee was a postdoctoral researcher at the Luddy School of Informatics, Computing, and Engineering at Indiana University. His work there centered on applying large-language models (LLMs) to model high-dimensional belief relationships, offering insights into the mechanisms of human belief formation and decision-making.

He received both his Ph.D. and B.Sc. in Physics from the Korea Advanced Institute of Science and Technology (KAIST), where he developed an interdisciplinary research portfolio spanning society, culture, and art through the lens of statistical physics and complex network science. His notable work, published in PNAS, applied information theory to analyze the evolution of landscape painting composition.