Research

I am interested in the following areas:

  • Bayesian methods
  • Biostatistics and Biological applications
  • Imaging analysis
  • Machine learning
  • Nonparametric and semiparametric inference
  • Causal inference
  • Sports analytics

I am an associate editor for Journal of the American Statistical Association, Annals of Applied Statistics, Statistica Sinica, Journal of Nonparametric Statistics, and Statistical Analysis and Data Mining: The ASA Data Science Journal. I used to serve on editorial board for PLOS ONE. See a recent post of my research on statistical applications here.,

I am the guest editor for a special issue on Bayesian nonparametrics at Journal of Nonparametric Statistics.  Please let me know if you’re interested or have any questions.

Publications:

Bayesian Statistics

  • with Dixit et al. (2024) Prediction Interval Transfer Learning for Linear Regression Using an Empirical Bayes Approach.
  • with Lan et al. (2024) Spatiotemporal Besov Priors for Bayesian Inverse Problems. [ArXiv]
  • with Pan et al. (2024) A Bayesian Approach for Selecting Relevant External Data (BASE): Application to a study of Long-Term Outcomes in a Hemophilia Gene Therapy Trial. [ArXiv]
  • Wang, J.,Shen, W., and Wang, Y. (2024) A Partially Collapsed Gibbs Sampling Algorithm for Regression with Misreported Response.
  • Zhu, W., Li, W., and Shen, W. (2023) Likelihood-free Gibbs Sequential Monte Carlo Sampling.
  • with Rice et al. (2023) Sparse Bayesian clustering of matrix data.
  • Pan, T., Shen, W., Davis-Stober, C. P., and Hu, G. (2023) A Bayesian nonparametric approach for handling item and examinee heterogeneity in assessment data. British Journal of Mathematical and Statistical Psychology. [Link]
  • Liu, C., Martin, R. and Shen, W. (2023) Empirical priors and posterior concentration in a piecewise polynomial sequence model. Statistica Sinica. [Link]
  • Shi, Y. and Shen, W.  (2023) Bayesian Methods in Tensor Analysis. Statistics and Its Interface.
  • Chen, K., Shen, W., and Zhu, W. (2023) Covariate Dependent Beta-GOS Process. Computational Statistics & Data Analysis, 180, 107662.
  • Banerjee, S. and Shen, W. (2022). Graph signal denoising using t-shrinkage priors. Journal of Statistical Planning and Inference, 219, 279-305.
  • Berman, B., Johnson, W. O., and Shen, W. (2021) Approximate Inferences for Bayesian Generalized Linear Regression Models.
  • Pan, T., Hu, G., and Shen, W. (2021) Identifying latent groups in spatial panel data using a Markov random field constrained product partition model. Statistica Sinica. [Link]
  • Berman, B., Johnson, W. O., and Shen, W. (2022) Normal approximation for Bayesian mixed effects binomial regression models. Bayesian Analysis, 1(1), 1-21.
  • Bi, J., Shen, W., and Zhu, W. (2022) Random Forest Adjustment for Approximate Bayesian Computation. Journal of Computational and Graphical Statistics, 31(1), 64-73.
  • Yin, F., Shen, W., and Butts, C. T. (2022) Finite Mixture of ERGMs for Modeling Ensembles of Networks. Bayesian Analysis, 17(4), 1153-1191. [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]

Neuroimaging and Machine Learning

  • Zhang, Y., Shen, W. and Kong, D. (2022) Covariance Estimation for Matrix-valued Data. Journal of the American Statistical Association.
  • Jiang, X. and Shen, W. (2023) Simultaneous denoising and heterogeneity learning for time series data. Statistics in Biosciences.
  • A Deep Graph Neural Networks Architecture Design: From Global Pyramid-like Shrinkage Skeleton to Local Link Rewiring (2020+) with Zhang et al.
  • Zhu, S., Shen, W. and Qu, A. (2022) Weighted AutoEncoding Recommender System. Statistical Analysis and Data Mining, 15(5), 570-585.
  • Hu, W., Kong, D. and Shen, W. (2019) Understanding neural network: a latent representer approach.
  • Gu, M. and Shen, W. (2020) Generalized probabilistic principal component analysis of correlated data. Journal of Machine Learning Research, 21(13): 1-41. [Link]
  • Gao, X., Shen, W., Shahbaba, B., Fortin, N. J. and Ombao, H. (2020) Evolutionary State-Space Model and Its Application to Time-Frequency Analysis of Local Field Potentials. Statistica Sinica. 30: 1561-1582. [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 classification. International Journal of Data Science and Analytics, 7(2):103-113[Link]
  • Hu, W., Pan, T., Kong, D., and Shen, W. (2021) Nonparametric Matrix Response Regression with Application to Brain Imaging Data Analysis. Biometrics, 77(4), 1227-1240.. [Link]
  • Hu, W., Shen, W., Zhou, H. and Kong, D.  (2020) Matrix Linear Discriminant Analysis. Technometrics, 62: 196-205.   [ArXiv]
  • Regularized matrix data clustering and its application to image analysis. (2021) with Gao et al. Biometrics, 77(3), 890-902. [Link]
  • Zhang, G., Li, G., Shen, W., and Zhang, W. (2020) The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos? Neurocomputing, 386: 8-17.
  • Gao, X., Shen, W., Ting, C.M., Cramer, S.C., Srinivasan, R. and Ombao, H. (2019) Estimating Brain Connectivity Using Copula Gaussian Graphical Models. In 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) (pp. 108-112). IEEE.
  • Gao, X., Shen W., Hu, J.,Fortin, N., Ombao, H. (2019) Modeling Local Field Potentials with Regularized Matrix Data Clustering. 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 597-602.
  • Suthaharan, S. and Shen, W. (2016) Pairing of most relevant variables and bootstrap samples with ridge regression for data sharing. 2016 IEEE Conference on Communications and Network Security (CNS).

Biostatistic methodology and applications

  • Clustering Computer Mouse Tracking Data with Informed Hierarchical Shrinkage Partition Priors. (2024) with Song et al. Biometrics.
  • Zhu, S., Shen, W., Fu, H. and Qu, A. (2023) Risk-aware Restricted Outcome Learning for Individualized Treatment Regimes of Schizophrenia. Annals of Applied Statistics.
  • Changes in Beat-to-Beat Blood Pressure and Pulse Rate Variability Following Stroke. (2023) with Abiri et al. Scientific Reports.
  • Survival Impact of Post-Operative Immunotherapy in Resected Stage III Cutaneous Melanomas in the Checkpoint Era. (2023) with Garo et al. ESMO Open.
  • Maternal Western-Style Diet Remodels the Transcriptional Landscape of Fetal Hematopoietic Stem and Progenitor Cells in Rhesus Macaques. (2022) with Sureshchandra et al. Stem Cell Reports.
  • Brazel, D., Kumar, P., Doan, H., Pan, T., Shen, W., Gao, L., & Moyers, J. T. (2023). Genomic Alterations and Tumor Mutation Burden in Merkel Cell Carcinoma. JAMA Network Open, 6(1), e2249674-e2249674.
  • Differential dynamics of peripheral immune responses to acute SARS-CoV-2 infection in older adults. (2021) with Lewis et al. Nature Aging, 1(11), 1038-1052.[Link]
  • Profiling of extracellular vesicle-bound miRNA to identify candidate biomarkers of chronic alcohol drinking in non-human primates. (2021) with Lewis et al. Alcoholism: Clinical and Experimental Research, 4121.
  • Obesity correlates with pronounced aberrant innate immune responses in hospitalized aged COVD-19 patients. (2021) with Zulu et al. Frontiers in Immunology. [Link]
  • Pan, T. Shen, W., and Hu, G. (2023) Clustering spatial functional data using a geographically weighted Dirichlet Process. Canadian Journal of Statistics.
  • Ethanol Drinking Induces Non-Specific Inflammation and Functional Defects in Alveolar Macrophages. (2022) with Lewis et al. American Journal of Respiratory Cell and Molecular Biology. [Link]
  • Ren, T., Shen, W., Zhang, L. and Zhao, H. (2021) Bayesian Phase II clinical trial design with noncompliance. Statistics in Medicine, 40(20), 4457-4472.
  • Gao, X., Shen, W., Ning, J., Feng, Z. and Hu, J. (2022) Addressing patient heterogeneity in disease predictive model development. Biometrics, 78(3), 1045-1055.
  • 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]

Sports analytics

  • with Xia et al. (2024) SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models. [arXiv]
  • with Xia et al. (2024) Language and Multimodal Models in Sports: A Survey of Datasets and Applications. [arXiv]
  • with Yang et al. (2024) Sports Intelligence: Assessing the Sports Understanding Capabilities of Language Models through Question Answering from Text to Video. [arXiv]
  • with Xia et al. (2024) SportQA: A Benchmark for Sports Understanding in Large Language Models. NAACL 2024 [arXiv]
  • with Xia et al. (2023) Advanced Volleyball Stats for All Levels: Automatic Setting Tactics Detection and Classification with a Single Camera. 23rd IEEE International Conference on Data Mining (ICDM). [arXiv]
  • with Price et al. (2022) How much does Home Field Advantage matter in Soccer Games? A causal inference approach for English Premier League analysis. [Link]
  • Wong-Toi, E., Yang, H.-C., Shen, W., and Hu, G. (2023) A Joint Analysis for Field Goal Attempts and Percentages of Professional Basketball Players: Bayesian Nonparametric Resource. Journal of Data Science, 21(1), 68–86.
  • Hu, G., Xue, Y., and Shen, W. (2022) Multidimensional heterogeneity learning for count value tensor data with applications to field goal attempt analysis of NBA players. [Link]
  • Yin, F., Hu, G., and Shen, W. (2023) Analysis of professional basketball field goal attempts via a Bayesian matrix clustering approach. Journal of Computational and Graphical Statistics, 32(1), 49-60. [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]

Others

  • A Model of Book Lovers’ Decisions on Goodreads.com. with Alantari et al. (2024)
  • Dai, M., Shen, W., and Stern, H. S. (2022) Sensitivity Analysis for the Adjusted Mann-Whitney Test With Observational Studies. Observational Studies, 8(1), 1-29.
  • Jiang, X., Livas, S., Yin, F., Banerjee, S., Butts, C. T. , and Shen, W. (2023) Structure recovery and trend estimation for dynamic network analysis. Stat.
  • Dai, M., Shen, W., and Stern, H. S. (2023) Nonparametric Tests for Treatment Effect Heterogeneity in Observational Studies. Canadian Journal of Statistics, 51(2), 531-558.
  • 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