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Jamie Coble

Professor

Dr. Jamie Baalis Coble is a Professor in the Department of Nuclear Engineering & Engineering Physics at the University of Wisconsin-Madison. Her research interests expand on past work in nuclear system monitoring and prognostics to incorporate system monitoring, equipment condition assessment, and remaining useful life estimates into risk assessment, operations and maintenance planning, and optimal control algorithms. Dr. Coble is currently pursuing research in applications of data analytics, machine learning, and artificial intelligence to support risk-aware, economic operations and maintenance of nuclear power facilities, as well as applications of these techniques in other domains such as nuclear security and advanced manufacturing.

Department

Nuclear Engineering & Engineering Physics

Contact

  • PhD 2010, University of Tennessee
  • MS 2009, University of Tennessee
  • MS 2006, University of Tennessee
  • BS 2005, University of Tennessee

  • Data-informed decision making
  • Operations and maintenance planning
  • Flexible concepts of operation
  • Supervisory control of nuclear systems
  • Operator and engineering support systems
  • Operator and engineering support systems

  • 2026 ANS HFICD, Hash Hashemian Mid-Career Award
  • 2025 UTK Graduate Student Senate, Outstanding Graduate Research Mentor Award
  • 2024 UTK Graduate Student Senate, Outstanding Graduate Research Mentor Award
  • 2021 UTK Tickle College of Engineering, Outstanding Service to the College Award
  • 2020 UTK Nuclear Engineering Department, Faculty Service Award
  • 2020 UTK Tickle College of Engineering, Professional Promise in Research Award
  • 2019 UTK Nuclear Engineering Department, Professor of the Year
  • 2018 UTK Commission for Women, Angie Warren Perkins Award
  • 2018 UTK Tickle College of Engineering, Leon and Nancy Cole Superior Teaching Award
  • 2017 ASEE Southeastern Section, New Faculty Research Award, Second Place
  • 2017 ANS HFICD, Ted Quinn Early Career Award
  • 2014 IEEE HST, Best paper awardf or “Towards a Theory of Autonomous Reconstitution of Compromised Cyber-Systems”
  • 2012 PNNL, Outstanding Performance Award (for work on LWRS NDE Roadmap)
  • 2012 PNNL, Outstanding Performance Award (for work on Ultrasonic Container Screening System)

  • Zanotelli, M., Ifeanyi, A., Mandelli, D., & Coble, J. (2026). Adaptation and Extension of a Margin-Based Approach for System-Level Health Assessment and Decision-Making. Nuclear Science and Engineering, 1-20.
  • Bairagi, A., Chen, M., Ifeanyi, A., Creasman, S., Coble, J., & Agarwal, V. (2026). Design of a SMART Valve Testbed for Nuclear Thermal Dispatch. Energies, 19(2), 470.
  • Ifeanyi, A. O., Zanotelli, M., & Coble, J. (2026). Explaining System-Level Prognostics with Established Machine Learning Methods. Nuclear Technology, 1-12.
  • Meilus, E. V., Lindsay, I. O., Coble, J., & Brown, N. R. (2026). Identification of Important Phenomena for Light Water Reactors During Heat Transport System Failure Events in Integrated Energy Systems. Nuclear Science and Engineering, 200(3), 653-663.
  • Worthy, J., Key, T. S., Morgan, S., & Coble, J. (2025). Development of a Python-Based Chemical Process Model for Legacy Slag Processing. In ANS Annual Conference.
  • Meilus, E., Lindsay, I., Coble, J., & Brown, N. (2025). Development of Safety Analysis Framework for a Pressurized Water Reactor (PWR) Integrated Energy System (IES) for Hydrogen Production. In ANS Annual Conference.
  • Zanotelli, M., Ifeanyi, A., Coble, J., & Mandelli, D. (2025). Comparative Analysis of Online Fault Tree and Margin-Based Approaches for System-Level Health Assessment and Decision-Making. In Nuclear Plant Instrumentation and Control & Human-Machine Interface Technology (NPIC&HMIT 2025).
  • Kochunas, B., Shen, Q., Coble, J., & Lindley, B. (2025). Demonstration of Methodology for Advanced Autonomous Control in Flexible Power Operation of Multi-Unit SMRs. In Nuclear Plant Instrumentation and Control & Human-Machine Interface Technology (NPIC&HMIT 2025).
  • Haste, D., Ghoshal, S., Hudson, J., Norton, C., Coble, J., Agarwal, V., & Hess, J. (2025). Digital Twin driven Nuclear Power Plant Health Monitoring, Diagnostics and Prognostics. In Nuclear Plant Instrumentation and Control & Human-Machine Interface Technology (NPIC&HMIT 2025).
  • Ifeanyi, A., & Coble, J. (2025). Enhancing System-Level Prognostics with Structural Information: A Graph-Based Approach. In 2025 IEEE International Conference on Prognostics and Health Management (ICPHM) (p. 1-8).