Irina Gaynanova
Associate Professor
Ann Arbor, Michigan, United States
Summary
👤
Senior🎓
Top SchoolIrina Gaynanova is an associate professor and statistician with a decade of experience developing computationally efficient, theoretically grounded methods for extracting low-dimensional structure from high-dimensional data. Her work spans multivariate analysis, machine learning, and convex-penalization techniques motivated by real-world problems such as leukemia classification from DNA methylation, antibiotic action via metabolomics, and false discovery control in sample-size planning. Having held faculty roles at Texas A&M and now University of Michigan after a Ph.D. from Cornell and an applied mathematics background from Moscow State University, she bridges domain collaboration and methodological innovation. Colleagues value her for translating challenging applied questions into new statistical tools that resist spurious correlations and over-selection while remaining computationally practical.
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 (31)
r-package10
monitors10
correlation10
truncated10
cgm10
ternary9
datasets9
stat9
sparse9
pressure9
robust8
jekyll7
version-control6
cran6
variable-selection6
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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