Hanyi Min

Hanyi Min is an Assistant Professor at the University of Illinois Urbana-Champaign with dual appointments in the School of Labor and Employment Relations and the Department of Psychology. Her research integrates psychometrics, organizational psychology, and machine learning to address critical challenges in human resources and employment relations.

Her primary research focuses on item response theory, measurement invariance across demographic variables, and machine learning applications for personnel selection. Key interests include employee turnover prediction, work passion validation, political diversity in organizations, and age-related measurement issues. She develops advanced psychometric techniques like item-focused trees to ensure fair assessment across diverse populations while leveraging recommender systems for workforce analytics.

Recent publications reveal a strong trend toward hybrid methodologies combining classical psychometrics with machine learning to solve practical HR problems. Her work emphasizes predictive validity in personnel selection, context-specific measurement invariance, and the socio-political dimensions of workplace diversity. Current research bridges psychological theory with computational approaches to improve organizational decision-making.