Irina Gaynanova is 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. Her teaching has been recognized with a Cornelia Ye Outstanding Teaching Assistant Award at Cornell University, she also serves as a faculty mentor in the Academy for Future Faculty at Texas A&M University.
Dr. Gaynanova’s research focuses on the development of statistical methods for analysis of modern high-dimensional biomedical data. Her main methodological interests are in the areas of statistical learning with sparsity, multivariate analysis and data integration. Her main application interests are in the analysis of multi-omics data and data from wearable devices, such as continuous glucose monitors and activity trackers. Her research has been supported by the National Science Foundation and recognized with a David P. Byar Young Investigator Award from the Biometrics section of the American Statistical Association and an NSF CAREER Award.