Yi Huang is currently an Associate Professor of Mathematics and Statistics at UMBC (University of Maryland, Baltimore County) and an affiliated faulty at School of Medicine, UMB. She got her Ph.D. degree in Biostatistics at the Johns Hopkins University Bloomberg School of Public Health in 2007. She got her M.S. degree in Atmospheric Science and graduate minor in Statistics at University of California, Los Angeles, in 2000, and completed her B.S. training in Atmospheric Physics at Peking University in 1997. She joined the Department of Mathematics and Statistics at UMBC in 2007 as a tenure-track Assistant Professor, to fulfill the need of the growing joint biostatistics graduate program
with the University of Maryland School of Medicine (UMB campus). The nature of biostatistics often requires interdisciplinary research at the interface between statistics and public health/ medicine/ biology.
As a biostatistician, her research is focused on applied statistical methodology resulting from public health oriented collaborations. Improving the public well-being is one of the most important research goals in her research. Her applied methodological research is centered on causal inference research and applied methods for comparative effectiveness research (CER), especially in propensity score related causal inference research and meta-analysis. Other research areas include: extending modern statistical design and analysis for evaluating personalized medicine (traditional chinese medicine), tolerance intervals, GLM, survival analysis, and longitudinal binary data. Her current collaborative research areas include post-marketing safety study and comparative effectiveness research, gerontology and aging studies, and mother/infant health (two vulnerable sub-populations in public health studies), precision medicine, and environmental health.