I recently completed my PhD in Statistics at Cornell University, where I was also an AI and Precision Nutrition (AIPrN) NIH T32 Predoctoral Fellow. During my PhD I worked with Dr. Martin T. Wells, Dr. Sumanta Basu, and Dr. Myung-Hee Lee on high-dimensional visualization, batch effect correction, and feature selection for longitudinal multi-omic data. My central contribution was a model called PROLONG designed to take a longitudinal clinical outcome and a high-dimensional set of longitudinal -omics predictors, returning a sparse set that co-vary with the outcome over time. My other work involved extending this method to include uncertainty quantification for linear models and to an EM-based approach to handling misclassified binary outcomes.
I finished my B.S. in Statistics at Texas A&M University in 2020. My primary advisor was Dr. Irina Gaynanova, who guided my development of the early versions of R package `iglu` and a corresponding Shiny App that handles metric calculations and visualizations for data from Continuous Glucose Monitors (CGMs).
