Assistant Professor, Epidemiology & Biostatistics Chao Huang is an Assistant Professor in the Department of Epidemiology & Biostatistics at the University of Georgia. He earned his Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill in 2019 and his B.S. in Applied Mathematics from Southeast University in 2008. His research centers on statistical learning for large-scale biomedical data, encompassing clinical, imaging, and genomic datasets. Dr. Huang develops novel statistical methods and machine learning algorithms—including deep learning approaches—for analyzing complex and heterogeneous data structures such as high-dimensional, functional, and manifold data. His work contributes to advancing understanding of disease progression and improving the design of clinical trials for treatment and early prevention. Current projects in his group involve big data integration, manifold and functional data analysis, imaging heterogeneity, imaging genetics, causal inference, and deep learning. Education: Ph.D. Biostatistics, University of North Carolina at Chapel Hill, 2019 B.S. Applied mathematics, Southeast University (China), 2008 Research Research Interests: Statistical learning of large-scale biomedical data (clinical, imaging, and genomic) Development of statistical methods and machine learning (deep learning) algorithms Analysis of complex data structures (high-dimensional, functional, manifold, and heterogeneous data) Big data integration Manifold data analysis Functional data analysis Imaging heterogeneity and imaging genetics Causal inference
