Faculty Profile

Veera Baladandayuthapani

Veera Baladandayuthapani, PhD

  • Chair, Biostatistics
  • Jeremy M.G. Taylor Collegiate Professor, Biostatistics
  • Director, Cancer Data Science Shared Resource
  • Associate Director, Quantitative Data Sciences
  • Joint Professor, Computational Medicine & Bioinformatics

Dr. Veera Baladandayuthapani is currently Jeremy M.G. Taylor Collegiate Professor and Chair in the Department of Biostatistics at University of Michigan (UM), where he also serves as the Associate Director of Associate Director of Quantitative Data Sciences and Director of the Cancer Data Science Shared Resource at UM Rogel Cancer Center.  He obtained his Ph.D. in Statistics from Texas A&M University (in 2005), M. A. in Statistics from University of Rochester (in 2000) and BSc in Mathematics from Indian Institute of Technology, Kharagpur in 1998. 

His research explores the potential of Bayesian probabilistic models and machine learning methods to assist in medical and health sciences. These methods are motivated by large and complex datasets such as high-throughput genomics, epigenomics, transcriptomics and proteomics as well as high-resolution neuro- and cancer- imaging. A special focus is on developing integrative and spatial models combining different sources of data for biomarker discovery and clinical prediction to aid precision/translational medicine. His work has resulted in 160+ papers published in top statistical, biostatistical, bioinformatics, biomedical & oncology journals. He has also co-authored a book on Bayesian analysis of gene expression data. 

He has received several prestigious awards that include being selected as Myrto Lefkopoulou Distinguished Lectureship from Harvard School of Public Health; H. O. Hartley award from the Department of Statistics at Texas A&M University; Theodore. G. Ostrom from Washington State University; MD Anderson Faculty Scholar Award; Young Investigator Award from the International Indian Statistical Association (IISA) and Editor's Invited Paper for Biometrics, a top biostatistics journal and the flagship journal of the International Biometrics Society.   He is a fellow of the American Association for Advancement in Science and the American Statistical Association and an elected member of the International Statistical Institute. He serves or has served on the Editorial board for major bio/-statistical journals such as Journal of American Statistical Association, Annals of Applied Statistics and Biometrics.

  • PhD, Statistics, Texas AandM University, College Station, TX, 2005
  • MA, Statistics, University of Rochester, Rochester, NY, 2000
  • BS, (Honors), Mathematics, Indian Institute of Technology (IIT), Kharagpur, India, 1999

Research Interests:
My statistical methodological interests are mainly in high-dimensional data modeling and Bayesian inference. This includes Bayesian bioinformatics, functional data analyses, graphical models, spatial models, Bayesian semi-/nonparametric models and machine learning. These methods are motivated by modern biomedical technologies generating large and complex-structured datasets such as high-throughput genomics, epigenomics, transcriptomics and proteomics as well as high-resolution neuro- and cancer- imaging. The core philosophy of my group is to leverage the underlying scientific hypotheses to be the motivating factors for development of new bio/statistical methodology.

Research Themes:
  • Spatial Biology
  • Multimodal data integration in cancer.
  • Bayesian graphical/network models
  • Cancer Imaging and Imaging-genomics. 

M4202 SPH II
1415 Washington Heights
Ann Arbor, MI 48103-2029

Administrative Assistant: Sabrina Olsson (siclayto@umich.edu)

Phone: (734) 764-5702
Email: veerab@umich.edu

Media inquiries: sph.media@umich.edu

Areas of Expertise: Biostatistics