Applications:
Biological Sciences, Healthcare Research
Methodologies:
Computing, Data Integration, Data Mining, Graph-Based Methods, Machine Learning, Mathematical and Statistical Modeling, Optimization, Statistics

Irina Gaynanova

Associate Professor

Biostatistics

Associate Professor, Biostatistics, School of Public Health

Dr. Gaynanova‚Äôs 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 (e.g., RNASeq, metabolomics, micribiome) and data from wearable devices (continuous glucose monitors, ambulatory blood pressure monitors, activity trackers).Dr. Gaynanova’s research has been funded by the National Science Foundation, and recognized with a David P. Byar Young Investigator Award and an NSF CAREER Award. She currently serves as an Associate Editor for Journal of the American Statistical Association, Biometrika and Data Science in Science.