Hui Jiang

Hui Jiang is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health. He holds a PhD in Computational and Mathematical Engineering from Stanford University (2009) and postdoctoral experience in statistical genomics at Stanford's Department of Statistics and Genome Technology Center. His research focuses on computational statistics, statistical genomics, and bioinformatics, with specialties in RNA-Seq data analysis, cancer genomics, and algorithmic development for resampling-based hypothesis testing.

Dr. Jiang's work emphasizes developing statistical methods for analyzing large-scale genomic data, including asymmetric data integration, penalized modeling, and efficient algorithms for p-value estimation. His contributions include software tools for RNA-Seq analysis (e.g., rSeqNP, rSeqDiff) and collaborative frameworks for biomedical data interpretation. He teaches courses on computing with big data (BIOSTAT625) and biostatistical fundamentals (EPID701).

Key research directions include statistical methods for cancer biomarker identification, high-dimensional data analysis, and optimization algorithms. His work bridges computational innovation with clinical applications, addressing challenges in precision health and precision oncology.