- Fisher 316
- 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
- Covariance matrix estimation and graphical modeling
- Kernel regression in machine learning
- High-dimensional data analysis
- Statistical inference with measurement error in covariates