Zuoheng Anita Wang, PhD

Dr. Wang is Associate Professor of Biostatistics and of Biomedical Informatics and Data Science at Yale University. Her research focuses on combining genetics, genomics, immunology, and statistical modeling to answer biologically important questions in genetic epidemiological studies. Dr. Wang's statistical expertise lies in longitudinal data analysis, varying coefficient models, mixed effects models, kernel machine methods, mediation analysis, machine learning methods, and network 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 breast cancer, alcohol and drug abuse, asthma, autism, obesity, lung and cardiovascular diseases. 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, addressing statistical challenges in single-cell RNA sequencing data and spatial transcriptomics, and machine learning for risk prediction in electronic health records data.