Dr. Jamie Baalis Coble is an Assistant Professor in the Nuclear Engineering department at the University of Tennessee, Knoxville. Dr. Coble’s expertise is primarily in statistical data analysis, empirical modeling, and advanced pattern recognition for equipment condition assessment, process and system monitoring, anomaly detection and diagnosis, failure prognosis, and integrated decision making. Her research interests expand on past work in monitoring and prognostics to incorporate remaining useful life estimates into risk assessment, operations and maintenance planning, and optimal control algorithms. Prior to joining the UT faculty, she worked in the Applied Physics group at Pacific Northwest National Laboratory. Her work there focused primarily on data analysis and feature extraction for detecting anomalies and degradation in large passive components, advanced active components, and nuclear fuel reprocessing systems. Dr. Coble is currently pursuing research in prognostics and health management for active components and systems; advanced control strategies for integration of small modular reactors with deep renewable penetration; and process monitoring and accountancy for safeguards of nuclear fuel cycle facilities.