Irina Gaynanova, PhD
She/Her
Associate Professor
Biostatistics, School of Public Health
Public Health
Irina Gaynanova is an Associate Professor in the Department of Biostatistics at University of Michigan. Prior to that, she was an Associate Professor of Statistifs at Texas A&M University. She received her PhD in Statistics from Cornell University in 2015. 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.
Projects:
integration of multi-omics data and microbiome data, statistical modeling of continuous glucose monitoring data
Research Area(s)
Biostatistics | Computational Data Science | Data science / Analytics / AI | Diabetes and management | Genetics / Genomics / other OMICS | Mathematical modeling & statistical analysis | Sensors and Wearables
Grants
- Principal investigator of: New machine learning methods for extracting features from digital health data with applications to sleep apnea
- Principal investigator of: Sensing physical activity to assess cancer risk from extreme heat
- Principal investigator of: The Impact of Sleep Apnea and Sleep Duration on Glycemic Profiles in Type 1 Diabetes Mellitus