Myungjin Kim works with Dr. Roberta De Vito on several projects for developing novel machine learning methods. The focus of his research is to develop the multi-study factor analysis methodologies to identify both common factors across multiple studies and study-specific factors for count data or data at different time points. He also aims to advance statistical methods based on a variational inference for joint analysis of multiple high-throughput biological studies. Myungjin received his Ph.D. from the Department of Statistics at Iowa State University in 2021, under the supervision of Dr. Lily Wang. During his Ph.D. studies, his primary research interests included non-/semi-parametric regression methods, spatial/spatiotemporal data analysis, quantile regression, functional and image data analysis.