Ruoyi Zhu is a Senior Quantitative Analyst based in Seattle with eight years of experience applying advanced statistical and measurement methods to high‑stakes assessment and cognitive health data. Holding a Ph.D. in Educational Measurement and Statistics from the University of Washington, Ruoyi has developed novel DIF and measurement invariance techniques—using lasso/group lasso with EM and GVEM—that materially improved detection rates compared with traditional tests. Their work spans applied problems for organizations like The College Board, Duolingo, and ADNI, and includes practical tools such as a Shiny app to make complex DIF analyses accessible to practitioners. Known for blending rigorous Bayesian and regularization approaches, Ruoyi brings both deep methodological expertise and a track record of translating research into validated, production‑ready solutions.
8 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Educational Assessment, Testing, and Measurement, Doctor of Philosophy - PhD, Educational Assessment, Testing, and Measurement at University of Washington
Contributions:433 commits, 116 pushes, 2 branches in 3 years 1 month
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