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Jun Ding.

Jun Ding

Research Associate Professor


Research

  • Design, simulation and monitoring of advanced reactors using digital twins; 
  • Instrumentation and control for autonomous nuclear systems;
  • Training machine learning for advanced reactor diagnosis technology.

Education

PhD, Nuclear Engineering, University of Tennessee, Knoxville, 2004
Thesis: Inferential Modeling and Independent Component Analysis for Redundant Sensor Validation

MS, Physics Entrepreneurship, Case Western Reserve University, 2002

MS, Nuclear Engineering, University of Cincinnati, 2000
Thesis: Monte Carlo Simulation of Compton Camera

BS, Nuclear Physics, University of Science and Technology of China, 1992


Professional Service

  • US Delegate Member of IEC SC45A WG9
  • Member of IEEE 1012 committee

Publications

Select List:

“Advanced Control Algorithms for Liquid Metal Reactors,” Coble, J.B., B.R. Upadhyaya, C. Briere, C.M. Walker, A.C. O’Connor, J.W. Hines, Y-C. Ko, J. Ding, 9th International Topical Meeting on Nuclear Plant Instrumentation, Control, & Human-Machine Interface Technologies. February 23-26, 2015, Charlotte, NC.

Software Verification and Validation Handbook for Digital I&C System in Nuclear Power Plant, Yang, S. and J. Ding, Xiamen University Press, 2010.

“Effective Software Verification and Validation Approach for Nuclear Power Plant Digital Instrumentation and Control Systems”, Yang, S., J. Ding, H. Miao, J. Zheng, Proceedings of the 18th International Conference on Nuclear Engineering,” May 17-21, 2010, Xi’an, China, ICONE18-29264.

“Independent Component Analysis for Redundant Sensor Validation,” Ding, J., J. W. Hines and B. Rasmussen, Proceedings of Maintenance and Reliability Conference (MARCON) 2003.

“Redundant Sensor Calibration Monitoring Using ICA and PCA,” Ding, J., A. Gribok, J. W. Hines and B. Rasmussen, Special issue of Real-time Systems on Applications of Intelligent for Nuclear Engineering, 2003.

Jun Ding.

Contact Information