Dr. Wang is Associate professor of Biostatistics at Yale School of Public Health. Her research focuses on combining genetics, genomics, immunology, and statistical modeling to answer biologically important questions in genetic epidemiological studies and cancer research. Dr. Wang's statistical expertise lies in kernel machine methods, mixed effects models, correlated data, and longitudinal data analysis. She develops statistically innovative methods and computationally efficient tools in large-scale genetic and genomic studies to identify genetic susceptibility variants and advance the understanding of the etiology of complex diseases including alcohol and drug abuse, asthma, obesity, cardiovascular diseases, and cancer. Current studies include using next-generation sequencing data to detect rare genetic variants in longitudinal genetic studies, combining knowledge in genomics and immunology to understand the risk of breast cancer survival, and differential gene expression in single-cell RNA sequencing data.