Hyun Min Kang

Hyun Min Kang is a Professor of Biostatistics at the University of Michigan School of Public Health. He specializes in developing statistical methods and computational tools for analyzing large-scale genomic data. His work focuses on spatial transcriptomics, single-cell genomics, and statistical approaches for genome-wide association studies (GWAS). Dr. Kang's research aims to understand the molecular basis of complex diseases using cutting-edge technologies like Seq-Scope for ultra-high-resolution spatial transcriptomics and tools like demuxlet/popscle for scalable single-cell analysis.

Education: PhD in Computer Science from UC San Diego (2009), MS and BS in Electrical Engineering from Seoul National University (2000/1998).

Research Interests: Spatial transcriptomics enables submicrometer resolution studies of gene expression dynamics. His lab develops tools to analyze sequence data (e.g., verifyBamID, GotCloud, Cramore) and has contributed foundational methods for GWAS through linear mixed models (EMMA/EMMAX). Recent projects include applications of spatial transcriptomics in liver and muscle tissues, and population-scale single-cell epigenomics.

Key Contributions: Pioneered methods for contamination detection in sequence data, developed widely used software (EPACTS, GEMMA), and advanced spatial genomics via Seq-Scope technology. His group's work on clonal hematopoiesis and rare variant analysis has implications for precision medicine.

Labs/Teams: Leads computational genomics efforts in the Biostatistics department, collaborating with labs like Jun G. Jun’s group on spatial transcriptomics and population-scale studies. Active in TOPMed and UK Biobank consortia.