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, doi:10.1002/env.2467, accepted.
  • Salazar, E., D. Hammerling, X. Wang, B. Sanso, A.O. Finley, and L. Mearns. (2016). Observation-based Blended Projections from Ensembles of Regional Climate Models. Climatic Change 138(1), 55-69, doi: 10.1007/s10584-016-1722-1.
  • Y. M. Ulrich-Lai, A. M. Christiansen,  X. Wang, S. Song, and  J.P. Herman. (2016). "Statistical modeling implicates neuroanatomical circuit mediating stress relief by 'comfort' food,''  Brain Structure and Function 221(6), 3141-3156, doi: 10.1007/s00429-015-1092-x. (PMID: 26246177)
  • 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.
  • M-O. Kim, X. Wang, C. Liu, K. Dorris, M. Fouladi,  and S. Song. (2016). "Random-effects meta-analysis for systematic reviews of Phase I clinical trials: rare events and missing data,'' accepted, Research Synthesis Methods.
  • K. Dorris, C. Liu, D. Li, T. Hummel, X. Wang, J. Perentesis, M-O Kim, M. Fouladi. (2017) “A comparison of safety and efficacy of cytotoxic versus molecularly-targeted drugs in pediatric phase I solid tumor oncology trials,” Pediatric Blood & Cancer 64(3), doi: 10.1002/pbc.26258.
  • K.L. Bennett, X. Wang, C.E. Bystrom, et al. (2015)  "The 2012 ABRF Proteomic Research Group Study: Assessing Longitudinal Intra-Laboratory Variability in Routine Peptide Liquid Chromatography Tandem Mass Spectrometry Analyses,"  Molecular & Cellular Proteomics 14(12):3299-3309
  • R. Slebos, X. Wang, X-J. Wang, B. Zhang, D. Tabb ,  D. Liebler. (2015). “Proteomic analysis of colon and rectal carcinoma using standard and customized databases,” Scientific Data 2, Article number: 150022 (2015), doi:10.1038/sdata.2015.22
  • 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. L. Tabb, X. Wang, S. A. Carr, et al. (2015). “Reproducibility of differential proteomic technologies in CPTAC fractionated xenografts”, Journal of Proteome Research 2016 Mar 4;15(3): 691--706, doi: 10.1021/acs.jproteome.5b00859. (PMID: 26653538)
  • 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).
  • X. Wang, M. C. Chambers, L. J. Vega-Montoto, D. M. Bunk, S. E. Stein, D. L. Tabb. (2014). "QC metrics from CPTAC raw LC-MS/MS data interpreted through multivariate statistics,'' Analytical Chemistry 86 (5), 2497-2509
  • P. A. Rudnick(*), X. Wang(*), E. Yan, N. Sedransk and S. E. Stein. (2014). “Improved Normalization of Systematic Biases Affecting Ion Current Measurements in Label-free Proteomics Data,” Molecular & Cellular Proteomics 13(5), 1341-1351. (* These authors contributed equally to this work.)
  • X. Wang and D. K. Dey. (2011). Generalized extreme value regression for ordinal response data. Environmental and Ecological Statistics 18(4), 619-634, DOI: 10.1007/s10651-010-0154-8
  • E. Salazar, B. Sansó, A. Finley, D. Hammerling, I. Steinsland, X. Wang and  P. Delamater. (2011). Comparing and blending regional climate model predictions for the American southwest. Journal of Agricultural, Biological, and Environmental Statistics, Special Issue: Computer Models and Spatial Statistics for Environmental Science 16(4), 586-605
  • X. Wang, D. K. Dey, and S. Banerjee. (2010). Non-Gaussian hierarchical generalized linear geostatistical model selection. In M-H Chen, D. K. Dey, P. Müller, D. Sun, and K. Ye (Eds.), Frontiers of Statistical Decision Making and Bayesian Analysis (pp. 484-496). Springer.
  • W. M. Dest, K. Guillard, S. L. Rackliffe, M-H Chen, and X. Wang. (2010). Putting green speeds: a reality check!. Applied Turfgrass Science.
  • X. Wang & D. K. Dey. (2010). Generalized extreme value regression for binary response data: an application to B2B electronic payments system adoption. Annals of Applied Statistics, 4(4), 2000-2023

Book Chapter

  • X. Wang (2017). ``Statistical Quality Assessment in MS/MS Proteomics'', Methods in Molecular Biology, Proteomics: Methods and Protocols. L. Comai, J. Katz, and P. Mallick (editors), 325–337, Springer Nature, New York. doi:10.1007/978-1-4939-6747-622.

Conference/Workshop Proceedings

  • Wang, Xia and Sedransk, Nell. (2011). "Bayesian models on biomarker discovery using spectral count data in the label-free shotgun proteomics,"  JSM 2011 Proceedings, 3445-3453

Presentations & Lectures

Invited Presentations

  • X. Wang, A. Shojaie, J. Zou (05/21/2013). Bayesian Large-Scale Multiple Testing for Time Series Data SAMSI 2012-2013 Transition Workshop on Massive Datasets Program, RTP, NC.
  • J. Pancras, X. Wang, and D.K. Dey (12/16/2013). Bayesian Mixture Modeling on Scale Heterogeneity and Customer Stochasticity EFaB@Bayes250, Durham, NC.
  • Wang, X. (05/16/2014). Big Opportunities in the Next Decade: SAMSI and NISS (invited panelist) Women in Statistics Conference, Durham, NC.
  • Wang, X. (05/16/2014). Bayesian Large-Scale Multiple Testing for Dependent Data Women in Statistics Conference, Durham, NC.
  • Wang, X. (06/16/2014). Bayesian Modeling of Ecological Count Data 2014 ICSA and KISS Joint Applied Statistics Symposium, Portland, OR.
  • Wang, X. (08/03/2014). Random-Effects Meta-Analysis for Rare Event Studies with No Within Study Comparator Joint Statistical Meetings 2014, Boston, MA.
  • Wang, X. (12/18/2014). Issues in Spatial-Temporal Modeling of Zero-Inflated Count Data The 24th Annual Conference of the International Environmetrics Society (TIES), Guangzhou, China.
  • Wang, X. (07/28/2015). Bayesian Hidden Markov Model in Large-Scale Multiple Testing 60th World Statistics Congress - ISI2015, Rio de Janeiro, Brazil.
  • Wang, X. (coauthor Duan, L.L. and Szczesniak, R.) (04-2016). Functional Gaussian Process for Large Scale Bayesian Nonparametric Analysis SSOR Department Seminar, Virginia Commonwealth University.
  • Wang, Xia (12/20/2016). A New Class of Cross-Covariance Function for Multivariate Spatial Data the 10th ICSA international conference, Shanghai, China.
  • Wang, Xia (10/22/2016). Mentoring ... and Giving Back Women in Statistics and Data Science, Charlotte, NC.
  • Wang, Xia (05/10/2016). Generalized linear regression models: How flexible it can and should be? Biostatistics Epidemiology & Research Design Monthly Seminar, Cincinnati, OH.

Paper Presentations

  • Wang, X. (08/11/2015). Bayesian Modeling for Change Point Detection in Longitudinal Clinical Proteomics Experiments. Joint Statistical Meeting, Seattle, WA.
  • Wang, X. (08/19/2014). Presence and Abundance of Atlantic Cod in Gulf of Maine: A Bayesian Approach. SAMSI 2014-2015 Mathematical and Statistical Ecology, RTP, NC.
  • Wang, X. (05/25/2014). A Hidden Markov Model for Multiple Hypothesis Testing. The 6th International Statistics Forum at Renmin University of China, Beijing, China.
  • X. Wang, M-H Chen, R.C. Kuo, D.K. Dey (08/04/2013). Bayesian Spatial-Temporal Modeling of Ecological Zero-Inflated Count Data. JSM, Montreal, Canada.
  • Wang, Xia (08/03/2016). Flexible link functions in nonparametric binary regression with Gaussian process priors. Joint Statistical Meetings, Chicago, IL.

Poster Presentations

  • X. Wang, A. Shojaie, J. Zou (08/12/2013). Bayesian Large-Scale Multiple Testing for Time Series Data ,” SAMSI 2013-2014 LDHD Summer School, RTP, NC.
  • J. Pancras, X. Wang, D.K. Dey (08/01/2013). Bayesian Mixture Modeling on Customer Stochasticity 15th IMS New Researchers Conference, Montreal, Canada.

Experience & Service

Work Experience

  • 2017Associate 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.


  • Reviewer, URC Faculty Program Reviewer