Mathematical Sciences

Mathematical Sciences

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Xia Wang

Title: Associate Professor, Statistics
Office: 4428E French Hall
Tel: 513-556-3295


  • Ph.D., University of Connecticut, 2009 (Statistics).
  • Ph.D., University of Connecticut, 2007 (Economics).

Research Information

Research Interests

Bayesian methodology and computation; Categorical data analysis; Scalable modeling of complex, high-dimensional data; Applications of statistical models in genomics and proteomics data.


Peer Reviewed Publications

  • L. L. Duan, R. D. Szczesniak, and X. Wang. (2017). “Functional inverted-Wishart for Bayesian multivariate spatial modeling with application to regional climatology model data”, Environmetrics 28 (7), doi:10.1002/env.2467.
  • D. Li *, X. Wang, & D. K. Dey. (2016). “A flexible cure rate model for spatially correlated survival data based on generalized extreme value distribution and Gaussian process priors,” Biometrical Journal 58(5), 1178–1197, doi: 10.1002/bimj.201500040.  (* graduate student supervised)
  • J. Pancras, X. Wang, and D. K. Dey. (2016). “Investigating the impact of customer stochasticity on firm price discrimination strategies using a new Bayesian mixture scale heterogeneity model,” Marketing Letters 27(3), 537-552, doi: 10.1007/s11002-015-9362-1.
  • X. Wang, M-H Chen, R. C. Kuo, and D. K. Dey. (2015). “Bayesian spatial-temporal modeling of ecological zero-inflated count data,” Statistica Sinica 25 (1), 189-204.
  • X. Wang, M-H Chen, R. C. Kuo, and D. K. Dey. (2016).  "Dynamic spatial pattern recognition in count data,''  Z. Jin et al. (eds.), New Developments in Statistical Modeling, Inference and Application, ICSA Book Series in Statistics, Springer International Publishing Switzerland, doi: 10.1007/978-3-319-42571-9_10, in press.
  • D. Li*, X. Wang, S. Song, N. Zhang, and D. K. Dey. (2015). “Flexible link functions in a joint model of binary and longitudinal data”, Stat, 4(1), 320--330. (* graduate student supervised.).
  • D. Li*, X. Wang, L. Lin, & D. K. Dey. (2015). “Flexible link functions in nonparametric binary regression with Gaussian process priors,''  Biometrics 72, 707–719, doi: 10.1111/biom.12462. (* graduate student supervised).

Presentations & Lectures

Invited Presentations

  • Wang, Xia (08/16/2017). Bayesian Hidden Markov Models for Dependent Large-Scale Multiple Testing, Bayesian Inference in Statistics and Statistical Genetics (The Third Annual Kliakhandler Conference), Houghton, MI.
  • Wang, Xia (04/22/2017). Scalable Massive Multivariate Data Modeling The 31st New England Statistics Symposium, Storrs, CT.
  • Wang, Xia (02/17/2017). Flexible Modeling in Generalized Linear Regression Models Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY.

Experience & Service

Work Experience

  • 2017- present, Associate Professor, University of Cincinnati, OH.
  • 2011 to 2017, Assistant Professor, University of Cincinnati, OH.
  • 2009 to 2011, Postdoctoral Fellow, National Institute of Statistical Sciences (NISS), NC.