Irina Gaynanova
Associate Professor
Ann Arbor, Michigan, United States
Summary
👤
Senior🎓
Top SchoolIrina Gaynanova is a seasoned statistics researcher and educator based in Ann Arbor, Michigan, and an Associate Professor at the University of Michigan, where she applies computational and theoretical methods to high-dimensional data. With a decade of university-level experience, her research spans multivariate analysis, machine learning, and penalization-based convex optimization to uncover meaningful low-dimensional structure in complex datasets. She places collaboration at the core of her work, translating challenging applied problems—such as classification of leukemia patients from DNA methylation profiles and controlling false discovery rates in sample size calculations—into robust statistical methodology. Her approach tackles spurious correlations and over-selection in high-dimensional settings by developing computationally efficient, theoretically sound techniques. She earned a PhD in Statistics from Cornell University and has trained internationally, including exchanges at the Technical University of Munich and study at Lomonosov Moscow State University.
10 years of coding experience
9 years of employment as a software developer
Exchange semester, Statistics, Exchange semester, Statistics at Technical University of MunichDoctor of Philosophy (Ph.D.), Statistics, Doctor of Philosophy (Ph.D.), Statistics at Cornell UniversityLomonosov Moscow State University
Russian, German
Github Skills (33)
r-package10
monitors10
correlation10
truncated10
cgm10
ternary9
datasets9
stat9
sparse9
pressure9
data-types8
robust8
jekyll7
version-control6
cran6
Programming languages (3)
Github contributions (5)
irinagain/iglu
Nov 2019 - Dec 2022
R package for Interpreting GLUcose data from CGMs (Continuous Glucose Monitors)
Contributions:5 releases, 16 reviews, 266 commits in 3 years 1 month
monitorsr-packagecontinuousglucose
StatisticalComputingClass/HW1
Aug 2020 - Aug 2022
Contributions:6 commits, 5 pushes in 2 years
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