Min Zhang

Min Zhang is a Professor of Statistics at Purdue University and Faculty Associate at the Center on Aging and the Life Course. His research focuses on Bayesian bioinformatics, genomics, and high-dimensional data analysis. He holds a joint appointment in the College of Science and has contributed to interdisciplinary projects in managed healthcare and proteomics.

• Education:
  • M.D., Hebei Medical University (1992)
  • M.S., Lanzhou University College of Medicine (1995)
  • Ph.D., Peking University Health Science Center (1998)
  • M.S., Cornell University (Biometry, 2003)
  • Ph.D., Cornell University (Biological Statistics & Computational Biology, 2005)

Research interests span computational biology, statistical genetics, and medical applications. Notable areas include metabolomic biomarker discovery, neuroimaging analysis, and crop genomics. His work integrates statistical theory with practical biomedical challenges.

Recent publications explore topics like Alzheimer's diagnostics via imaging, rice ionome genetics, and metabolomic profiling in colorectal cancer. He has developed statistical tools like the 2DCOW algorithm for data alignment and penalized regression methods for genetic studies.

• Awards:
  • Seed for Success Award (2009)
  • College of Science Interdisciplinary Award (2009)
  • Liu Memorial Award (2005)

Advised notable students including Chen Chen (PhD) and Vitara Pungpapong (PhD). Active in grants for genomic selection and metabolomics. Leads the Statistical Bioinformatics group at Purdue, collaborating with institutions like Seven Bridges and the City of Hope Beckman Research Institute.

Labs/Teams: Involved in the Purdue Center on Aging, the Indiana University Center for Medical Genomics, and the Computational Genomics Core at the Beckman Research Institute.