Dr. Gaynanova's research focuses on statistical methods for 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, in particular data from continuous glucose monitors (CGMs). Most of her research is collaborative and interdisciplinary in nature, with the ultimate goal of improving individual health outcomes.
- Ph.D, Statistics, Cornell University
- M.S., Statistics, Cornell University
- M.S., Applied Mathematics and Computer Science, Lomonosov Moscow State University
Health Services Research and Policy Focus
Condition Focus
Affiliated Centers and Programs
U-M Academic Affiliation(s)
Public Health
Public Health
Biostatistics
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U-M Primary Appointment
Associate Professor
Public Health » Biostatistics
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