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Jamie Coble

Jamie B. Coble

Southern Company Faculty Fellow, Associate Professor, and Assistant Head for Undergraduate Studies and Service


University of Tennessee
August 2013 to August 2019 
Assistant Professor

  • Building a research program in empirical modeling methods for process and equipment monitoring, anomaly detection and diagnostics, and prognostics

August 2019 to Present
Associate Professor

Pacific Northwest National Laboratory
June 2011–July 2013
Scientist, Applied Physics, Acoustics, and Ultrasonics

  • Work with multidisciplinary teams to perform research in process monitoring and equipment health assessment, primarily for nuclear systems
  • Project manager for the Multi-Isotope Process (MIP) Monitor, an automated, real-time process monitoring tool for used nuclear fuel reprocessing systems
  • Primary research projects include online monitoring for sensor calibration and signal validation, risk monitors with real-time equipment condition assessment for aSMRs, MIP Monitor development, reconstitution methods for cyber systems, and prognostic algorithm development for passive nuclear power plant components and structures.

University of Tennessee
Assistant Research Professor
December 2010–May 2011

  • Taught courses in artificial intelligence and advanced modeling techniques
  • Facilitated and managed a research group of approximately ten graduate students (PhD- and MSlevel) in the PI's absence
  • Continued research in system monitoring for fault detection, diagnostics, and prognostics

May 2010–December 2010
Postdoctoral Researcher

  • Performed tasks for completion of NERI-C research in health monitoring for small modular reactors
  • Mentored and assisted graduate student researchers working in the area of health monitoring

January 2005–May 2010
Research Assistant

  • Developed a MATLAB-based Process and Equipment Prognostics (PEP) Toolbox
  • Developed and defined metrics for characterizing the suitability of candidate prognostic parameters and associated methods for automatic identification of prognostic parameters
  • Performed research in empirical techniques for monitoring, fault detection, diagnostics, and prognostics for physical and electronic systems


PhD, Nuclear Engineering, University of Tennessee, 2010

MS, Reliability and Maintenance Engineering, University of Tennessee, 2009

MS, Nuclear Engineering, University of Tennessee, 2006

BS, Nuclear Engineering and Mathematics, University of Tennessee, 2005

Professional Service

Member of American Nuclear Society, Institute of Nuclear Material Management, Institute of Electrical and Electronics Engineers, and Tau Beta Pi

Currently serving on the executive committee of the ANS Human Factors, Instrumentation and Control Division (HFICD)

Participated in International Atomic Energy Agency (IAEA) Coordinated Research Programme (CRP) on Advanced Surveillance, Diagnostics and Prognostics Techniques Used for Health Monitoring of Systems, Structures, and Components in Nuclear Power Plants

Chaired sessions at ANS Annual and Winter Meetings and various international conferences


Coble JB, P Ramuhalli, RM Meyer, and H Hashemian. 2013. "Online Sensor Calibration Assessment in Nuclear Power Systems," IEEE Instrumentation and Measurements Magazine16(3): 32–37.

J.B. Coble and J.W Hines. 2013. "Identifying Suitable Degradation Parameters for IndividualBased. Prognostics." In S. Kadry (Ed.), Diagnostics and Prognostics of Engineering Systems: Methods and Techniques. Pp 135–150. Hershey, PA: IGI Global.

Coble JB, P Ramuhalli, LJ Bond, W Hines, and B Upadhyaya. 2012. "Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications," PNNL-21515, Pacific Northwest National Laboratory, Richland, WA.

Coble JB, RM Meyer, P Ramuhalli, LJ Bond, H Hashemian, B Shumaker, and D Cummins. 2012. "A Review of Sensor Calibration Monitoring for Calibration Interval Extension in Nuclear Power Plants," PNNL-21687, Pacific Northwest National Laboratory, Richland, WA.

Coble, J. and J.W. Hines. 2011. "Applying the General Path Model to Estimation of Remaining Useful Life," International Journal of Prognostics and Health Management 2, (1): 007.

Jamie Coble

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