Min Wang, Ph.D.

Associate Professor of Management Science and Statistics


  • Ph.D. Clemson University
  • M.S. Clemson University
  • B.A. Concordia University


Min Wang is an associate professor of statistics in the Department of Management Science and Statistics at The University of Texas at San Antonio. He previously worked at Michigan Technological University and Texas Tech University. His primary research interests center on Bayesian statistics, high-dimensional inference and statistical machine learning. His work has been published in Bayesian Analysis, Bernoulli, Computational Statistics and Data Analysis, Journal of Statistical Planning and Inference, The American Statistician, etc. Dr. Wang has also collaborated with researchers from biological sciences, biomedical engineering, civil engineering, mechanical engineering, social sciences and other related fields. His collaborative work has been published in Construction and Building Materials, Journal of Applied Physiology, Journal of Manufacturing Processes, Physics in Medicine and Biology, Soil Science Society of America Journal, etc. Dr. Wang’s research was partially supported by funding from National Institute of Health, National Science Foundation and other agencies.

Research Interests

  • Bayesian statistics
  • High dimensional inference
  • Statistical consulting
  • Statistical machine learning

Recent Publications

  • “Objective Bayesian testing for the correlation coefficient under divergence-based priors,” with B. Peng, The American Statistician, forthcoming.
  • “The minimum Bayes factor hypothesis test for correlations and partial correlations, with F. Chen and K. Ye, Communications in Statistics – Theory and Methods, forthcoming.
  • “Multivariate analysis of variance (MANOVA) on the microstructure gradient of biomimetic nanofiber scaffolds fabricated by cone electrospinning,” with Y. Zhou and G. Tan, Journal of Manufacturing Processes, Vol. 44, 2019, pp. 55-61.
  • “Posterior consistency of g-prior for variable selection with a growing model size,” with Y. Mayurama, Journal of Statistical Planning and Inference, Vol. 196, 2018, pp. 19-29.
  • “Bayesian variance changepoint detection in linear models with symmetric heavy-tailed errors,” with S. Kang, G. Liu and H. Qi, Computational Economics, Vol. 52, 2018, pp. 459-477.
  • “Asymptotic properties for fractional integral processes with jumps and noise,” with G. Liu and L. Zhang, Statistics: A Journal of Theoretical and Applied Statistics, Vol. 52, 2018, pp. 1156-1192.
  • “Sympathetic neural reactivity to mental stress differs in black and non-Hispanic white adults,” with I. Fonkoue, C. Schwartz and J. Carter, Journal of Applied Physiology, Vol. 124, 2018, pp. 201-207.
  • “Mixtures of g-priors for analysis of variance models with a diverging number of parameters,” Bayesian Analysis, Vol. 12, 2017, pp. 511-532.
  • “Consistency of Bayes factor for nonnested model selection when the model dimension grows,” with Y. Mayurama, Bernoulli, Vol. 22, 2016, pp. 2080-2100.