Irina Gaynanova is an Associate Professor in the Department of Biostatistics at University of Michigan. She received her PhD in Statistics from Cornell University in 2015.
Dr. Gaynanova’s teaching methods emphasize reproducible research practices, statistical computing and communication skills; her goal being to prepare students for STEM-oriented careers.
Dr. Gaynanova’s research focuses on the developing statistical methods for analyzing modern high-dimensional biomedical data. Her methodological interests are in data integration, machine learning and high-dimensional statistics, motivated by challenges arising in analyses of multi-omics data and data from wearable devices, focusing on data from continuous glucose monitors. Her research has been funded by the National Science Foundation and the National Institutes of Health, and recognized with a David P. Byar Young Investigator Award and an NSF CAREER Award. Dr. Gaynanova is a elected member of the International Statistical Institute and serves on the editorial board of the Annals of Applied Statistics, Biometrika, Data Science in Science, and Journal of the American Statistical Association.