معرفی
Irina Gaynanova is an Associate Professor in the Department of Biostatistics at the University of Michigan School of Public Health. She also holds a courtesy appointment in the Department of Statistics. Her research focuses on developing statistical methods for analyzing high-dimensional biomedical data, particularly in multi-omics and wearable device data (e.g., CGMs). Her work has been funded by the NSF and recognized with awards like the NSF CAREER Award and COPSS Emerging Leader Award.
Education: PhD in Statistics from Cornell University (2015), MS from Cornell (2013), and a Diploma in Applied Math/Computer Science from Lomonosov Moscow State University (2009).
Research Interests: High-dimensional data analysis, machine learning, data integration, multi-omics data, and wearable device data such as continuous glucose monitors. She leads a research group with active students and postdocs, emphasizing reproducible research and collaboration with domain scientists.
Awards: Includes the David P. Byar Young Investigator Award, IMS Zelen Award (2025), and COPSS Emerging Leader Award (2025). She is an elected member of the International Statistical Institute (2024).
Teaching & Mentoring: Focuses on computational skills and reproducible research. Received the Dr. Judith Edmiston Mentoring Award for undergraduate mentoring at Texas A&M.
Labs/Teams: Leads the Gaynanova Lab, which develops tools like the iglu R package for CGM data analysis and collaborates on projects involving microbial networks, sleep apnea, and precision health.
