Selene Schmittling is a Ph.D. student in the EnBiSys Lab, within the Department of Electrical and Computer Engineering at NC State. Her research focuses on developing interpretable, data-driven machine-learning models to understand how plants react to stress and hormones. Recent work using static and temporal data, and logistic regression models with LASSO uncovered transcription factors likely controlled outside of transcription that are involved in iron deficiency response in Arabidopsis thaliana root epidermis. Future work involves comparative network analysis to identify differences in networks developed using transcriptional vs. translational data. Selene is an Initiative for Maximizing Student Diversity (IMSD) Fellowship Fellow.