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Research interests
My main research is currently in Bayesian statistics, particularly Bayesian nonparametric models, Approximate Bayesian Computation and other methods dealing with intractable likelihood. I am interested in applying those models in ecology and epidemiological science.

Journal Publications:
8.Bi J, Shen W, Zhu W. (2022). Random Forest Adjustment for Approximate Bayesian Computation. Journal of Computational and Graphical Statistics, 31(1), 64-73. Link.
7.Dalla Valle, L., Leisen, F., Rossini, L., & Zhu, W. (2021). A Pólya–Gamma sampler for a generalized logistic regression. Journal of Statistical Computation and Simulation, 91(14): 2899-2916. Link
6.Dalla Valle, L., Leisen, F., Rossini, L., & Zhu, W. (2020). Bayesian analysis of immigration in Europe with generalized logistic regression. Journal of Applied Statistics, 47(3), 424-438. Link
​5.Cassese, A; Zhu, W; Guindani, M; Vannucci, M. (2019). A Bayesian Nonparametric Spiked Process Prior for Dynamic Model Selection. Bayesian Analysis, 14 , no. 2, 553--572. Link
4. Zhu W, Leisen F, Marin J.M. (2016). A Bootstrap Likelihood approach to Bayesian Computation,  Australian and New Zealand Journal of Statistics, 58, 227--244.​ Link
3. 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.
2. Zhu W, Leisen F. (2015). A multivariate extension of a vector of two-parameter Poisson-Dirichlet processes", Journal of Nonparametric Statistics. Volume 27, Issue 1, 89-105. Link
1. Wang J, Liu D, Zhang H, Zhu W, Dong Z, Zang Y. (2013). Asymmetry of the dorsal anterior cingulate cortex: evidences from multiple modalities of MRI. Neuroinformatics. April 2013, Volume 11, Issue 2, pp 149-157. Link
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