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I am a Ph.D. student in biostatistics at UCLA, working in Marc Suchard's group. Before coming to UCLA, I received my bachelor's degree from Department of Biomedical Engineering at Peking University, China in 2016.
Contact me at: zy.zhang[at]ucla.edu
My research interest is in Bayesian inference and computation with applications to phylogenetics (the study of evolutionary relationships among species, genes, etc). In phylogenetics, the observations are correlated via the shared evolutionary history of individuals and highly complex models are required to control for the underlying phylogenetic tree structure. I enjoy developing efficient inference methods to deal with the computational challenges arising from these complex models. All our works are implemented in the widely used BEAST software.
Current Project - Efficient Inference for Phylogenetic Multivariate Probit Models
We develop a new computation approach for inferring correlation among binary and continuous biological features, while controlling for the uncertain phylogenetic tree. Compared to previous studies we reduce the complexity from quadratic to linear order in sample size. In one application, we examine the correlation among 25 HIV epitopes and virulence measures across 535 viruses.