Irina Gaynanova is an Associate Professor in the Department of Biostatistics at University of Michigan. Prior to that, she was an Associate Professor in the Department of Statistics at Texas A&M University. 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 development of statistical methods for analysis of 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. Her research has been funded by the National Science Foundation, and recognized with a David P. Byar Young Investigator Award and an NSF CAREER Award.