I am interested in the following areas:

  • Bayesian methods
  • Biostatistics
  • Biological applications
  • Big data
  • Imaging
  • Statistics theory and machine learning

See a recent post on my research on statistical applications here


Bayesian Statistics

  • Bi, J., Shen, W., and Zhu, W. (2019) Random Forest Adjustment for Approximate
    Bayesian Computation.
  • Yin, F., Shen, W., and Butts, C. T. (2019) Finite Mixture of ERGMs for Modeling Ensembles of Networks.
  • Martin, R. and Shen, W. (2017+) Asymptotically optimal empirical Bayes inference in a piecewise constant sequence model. Under review.  [Link]
  • Shen, W. and Ghosal, S. (2017) Posterior Contraction Rates of Density Derivative Estimation. Sankhya A, 79(2), 336-354 (invited paper). [Link]
  • Shen, W., Ning, J. and Yuan, Y. (2016) Rate-adaptive Bayesian independent component analysis. Electronic Journal of Statistics, 10(2): 3247-3264. [Link]
  • Shen, W. and Ghosal, S. (2016) Adaptive Bayesian density regression for high-dimensional data. Bernoulli, 22(1): 396-420. [PDF]
  • Shen, W. and Ghosal, S. (2015) Adaptive Bayesian procedures using random series priors. Scandinavian Journal of Statistics, 42(4): 1194-1213. [PDF]
  • Shen, W., Tokdar, S. T. and Ghosal, S. (2013) Adaptive Bayesian multivariate density estimation with Dirichlet mixtures. Biometrika, 100(3): 623-640. [PDF]

Biostatistic methodology and applications

  • Gao, X., Shen, W., Ning, J., Feng, Z. and Hu, Jianhua (2019+) Addressing patient heterogeneity in disease predictive model development.
  • Shen, W., Liu, S., Chen, Y., and Ning, J. (2019) Regression analysis of longitudinal data with outcome-dependent sampling and informative censoring. Scandinavian Journal of Statistics, 46(3): 831-847. [Link]
  • Shen, W., Ning, J., Yuan, Y., Lok, A. and Feng, Z. (2018) Model-free scoring system for risk prediction with application to hepatocellular carcinoma study. Biometrics, 74: 239-248. [Link]
  • Shen, W., Ning, J. and Yuan, Y. (2015) A direct method to evaluate the time-dependent predictive accuracy for biomarkers. Biometrics, 71: 439-449.  [Link]
  • Shen, W., Ning, J. and Yuan, Y. (2015) Bayesian sequential monitoring design for two-arm randomized clinical trials with noncompliance. Statistics in Medicine, 34: 2104-2115. [Link]

Single cell analysis and modeling

  • Single Cell Transcriptomic Analyses of Cell Fate Transitions during Human Cardiac Reprogramming. (2019) with Zhou et al. Cell Stem Cell, 25(1): 149-164. [Link]
  • Lin28a Regulates Pathological Cardiac Hypertrophic Growth through Pck2-mediated Enhancement of Anabolic Synthesis. (2019) with Ma, H. et al. Circulation, 139: 1725-1740. [Link]
  • Single cell transcriptomics reconstructs fate conversion from fibroblast to cardiomyocyte. (2017) with Liu et al. Nature, 551(7678):100-104. [Link]

Neuroimaging and Machine Learning

  • Hu, W., Kong, D. and Shen, W. (2019) Understanding neural network: a latent representer approach.
  • Gu, M. and Shen, W. (2019+) Generalized probabilistic principal component analysis of correlated data. Journal of Machine Learning Research. Accepted. [Link]
  • Gao, X., Shen, W., Shahbaba, B., Fortin, N. J. and Ombao, H. (2018+) Evolutionary State-Space Model and Its Application to Time-Frequency Analysis of Local Field Potentials. Statistica Sinica. Accepted. [ArXiv]
  • Kong, D., Bondell, H., and Shen, W. (2018) Outlier Detection and Robust Estimation in Nonparametric Regression. Journal of Machine Learning Research W&CP (AISTATS), 84:208-216. [Link]
  • Suthaharan, S. and Shen, W. (2019) Elliptical modeling and pattern analysis for perturbation models and classfication. International Journal of Data Science and Analytics, 7(2):103-113[Link]
  • Hu, W., Kong, D., and Shen, W. (2019+) Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis. Under review. [ArXiv]
  • Hu, W., Shen, W., Zhou, H. and Kong, D.  (2019) Matrix Linear Discriminant Analysis. TechnometricsAccepted.   [ArXiv]
  • Regularized matrix data clustering and its application to image analysis. (2018+) with Gao et al.
  • Zhang, G., Li, G., Shen, W., and Zhang, W. (2019+) The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos? Neurocomputing. Accepted.
  • Gao, X., Shen, W., Ting, C., Cramer, S., Srinivasan, R., Ombao, H. (2018+) Estimating Brain Connectivity using Copula Gaussian Graphical Models.


  • Nipoti, B. and Shen, W. (2018) Discussion: Bayesian Cluster Analysis: Point Estimation and Credible Balls. Bayesian Analysis.
  • Gao, X., Shen, W. and Ombao, H. (2018) Discussion: The statistical analysis of acoustic phonetic data: exploring differences between spoken Romance languages. Journal of the Royal Statistical Society, Series C
  • Shen, W. and Kong, D. (2016) Discussion: Statistical modelling of citation exchange between statistics journals. Journal of the Royal Statistical Society: Series A.
  • Ren, H., Shen, W., Wu, R. and Soo, Y. (2013) Moment estimation based on quantiles. WIREs Computational Statistics, 5(5): 387-390.
  • Zhu, W. and Shen, W. (2016) Discussion of “Perils and potentials of self-selected entry to epidemiological studies and surveys”. Journal of the Royal Statistical Society: Series A