Sunbeom Kwon

I am a Ph.D. candidate in the Quantitative Psychology program at the University of Illinois Urbana-Champaign. I earned an M.S. in Statistics from the University of Illinois Urbana-Champaign and an M.A. in Psychology from Sungkyunkwan University.

I am broadly interested in psychometrics and data science. My current research focuses on three core objectives:

1. Copula-based Latent Variable Models I develop copula-based methods to improve measurement accuracy and enable hypothesis testing for non-linear and asymmetric dependence of latent variables. This overcomes traditional multivariate Gaussian assumptions, allowing for a more flexible and nuanced dependence structure.

2. Integrating Psychometrics and AI My work explores the bidirectional interaction between these fields: I apply measurement theory to evaluate the performance and fairness of AI systems, while also utilizing modern AI techniques to improve the accuracy and efficiency of complex psychometric models.

3. Analyzing Complex Modern Testing Data I create frameworks for extracting meaningful insights from unstructured and noisy “process data,” such as computer log files. These methods are designed to support robust statistical inference from information-rich, high-dimensional data sources.