Dr. Dillon Pruett is an Assistant Professor in the School of Communication Science and Disorders whose research bridges clinical informatics, statistical genomics, and artificial intelligence in the study of the neurobiological underpinnings of stuttering and related conditions. He leverages machine learning and natural language processing approaches to mine electronic health records (EHRs) and utilizes biobank datasets to map the genetic risk architecture of stuttering. Expanding on these computational frameworks, Dr.

Dr. Uejio's research develops novel societal determinants of health datasets. His team is constructing the nation's first property-level residential housing quality dataset using property records and explainable machine learning (XGBoost/SHAP) for nationwide estimates. They also map local Adverse Childhood Experiences (ACEs) using electronic health records.