Byung-Jun Kim

Byung-Jun Kim


  • Assistant Professor, Mathematical Sciences
  • PhD, Statistics, Virginia Tech
  • BS/MS, Statistics, Chung-Ang University


Byung-Jun Kim received his PhD from Statistics at Virginia Tech in 2020. After his graduation, he joined the Department of Mathematical Sciences at Michigan Technological University as a tenure-track assistant professor in August 2020.

His core research interests focus on developing statistical methodologies within nonparametric and semiparametric regression frameworks for complex observational data, especially high-dimensional data and measurement error. His specific research topics include Gaussian graphical modeling, kernel machine learning-based regression, and omnibus hypothesis testing method for measurement error and high-dimensional data arising in any domain of epidemiology, genomics, and engineering.

Areas of Expertise

  • Multivariate data analysis
  • Semiparametric regression for functional estimation
  • Variable selection

Research Interests

  • Covariance matrix estimation and graphical modeling
  • Kernel regression in machine learning
  • High-dimensional data analysis
  • Statistical inference with measurement error in covariates