Hua Zhou

Hua  Zhou Ph.D.

  • Faculty

Dr. Hua Zhou, Professor of Public Health, has long term interests in numerical optimization problems, particularly those arising from statistical analysis of high-dimensional data. He developed highly scalable optimization algorithms for maximum likelihood estimation of some multivariate discrete distributions, calculation of importance sampling weights for large data sets, geometric and signomial programming, and a model-based movie rating method. He also proposed a new deterministic annealing method for global optimization, a quasi-Newton scheme for accelerating high-dimensional optimization algorithms, and a strategy for massive parallel computing using graphical processing units (GPUs). He studied new path following algorithms for regularization problems in statistics and machine learning, and successfully generalized them to least angle regression and convex programming. His recent development also includes scalable estimation algorithm for multivariate response generalized linear models and variance components models, fast matrix computation tools, and distance majorization for convex programming.

One of Dr. Zhou's research interests is to develop statistical and computational tools for analysis of large-scale genomic data. He developed penalization methods for association screening of genome-wide association (GWAS) and next generation sequencing (NGS) data, and a nonlinear dimension reduction approach for genotype aggregation and association mapping. Currently he is working on genome-wide QTL association mapping based on family designs, genotype imputation, transcriptomics data analysis based on RNA-seq technology, and statistical methods for analyzing microbiome data. Dr. Zhou is a developer of the comprehensive genetics analysis software Mendel, which is freely available at the UCLA Human Genetics Software Page. His current work includes implementing fast likelihood ratio test of variance components for genome wide QTL mapping and fast genotype imputation for pedigrees.

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