I am a PhD Candidate at Cornell University and an AI and Precision Nutrition (AIPrN) NIH T32 Predoctoral Fellow. During my PhD I have 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 main contribution up to this point is 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. I am now interested in various extensions to PROLONG as well as general tensor models, both having broad applications to multi-omic data and precision nutrition.
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).
