Selene Schmittling is a former Ph.D. student in the EnBiSys Lab at NC State, and also was an Initiative for Maximizing Student Diversity (IMSD) Fellow. Her research focused on developing interpretable, data-driven machine-learning models to understand how plants react to stress and hormones. For example, she used static and temporal data, and logistic regression models with LASSO to uncovered transcription factors, likely controlled outside of transcription, that are involved in iron deficiency responses in Arabidopsis thaliana root epidermis.