Irina Gaynanova is an Associate Professor in the Department of Biostatistics at the University of Michigan. She received her PhD in Statistics from Cornell University in 2015.
Dr. Gaynanova’s teaching emphasizes reproducible research practices, statistical computing, and communication skills to prepare students for STEM careers.
Her research focuses on developing statistical methods for analyzing high-dimensional biomedical data. Her methodological interests include data integration, machine learning, and high-dimensional statistics, driven by challenges in multi-omics analyses and wearable device data, particularly continuous glucose monitors. Her research has been funded by the National Science Foundation and the National Institutes of Health, and she served on the editorial boards of the Annals of Applied Statistics, Biometrika, Data Science in Science, the Journal of the American Statistical Association, and the Journal of Computational and Graphical Statistics.
Her contributions to research, teaching, mentorship, and service have been recognized with a David P. Byar Young Investigator Award, an NSF CAREER Award, elected membership to the International Statistical Institute, the IMS Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award and the COPSS Emerging Leader Award.