Assistant Professor
Biography
Zhao received his PhD in nuclear science and engineering from Massachusetts Institute of Technology. Zhao's research interests span multiple disciplines of nuclear energy systems—with emphasis on thermal hydraulics and I&C—and their intersections with artificial intelligence and decision science. He has been a major contributor to a diverse portfolio of DOE, NRC, and ORNL funded projects that advance the state of the art of modeling and simulation and digital engineering for applications in both legacy and next-generation reactors. He has authored more than 50 publications and has led seven successful proposals with total funding of $10M.
Research
Zhao's research interests span multiple disciplines of nuclear energy systems—with emphasis on thermal hydraulics and instrumentation and controls (I&C)—and their intersections with artificial intelligence (AI) & machine learning (ML) and decision science. He has been a major contributor to a diverse portfolio of research projects that advance the state of the art of modeling & simulation and digital engineering for applications in both legacy and next-generation nuclear reactors. He has authored more than 50 publications and has led or contributed to successful proposals of $10M total funding from the U.S. Department of Energy and Oak Ridge National Laboratory.
- Computational thermal hydraulics, prognostics and health management, autonomous control, systems engineering, safety and reliability analysis
- AI & ML for nuclear and thermal-fluid systems, digital twin, validation and verification, uncertainty quantification, optimization, high performance computing
- Techno-economic analysis, life cycle assessment, hybrid/integrated energy systems
Education
PhD, Nuclear Science and Engineering, Massachusetts Institute of Technology, 2019
MS, Nuclear Science and Engineering, Massachusetts Institute of Technology, 2016
Dipl. Ing., Nuclear Engineering, National Institute for Nuclear Science and Technology (INSTN), Saclay, France, 2014
Dipl. Ing., Energy and Environmental Engineering, National Institute of Applied Sciences (INSA), Lyon, France, 2014
Professional Service
Member of the American Nuclear Society (ANS) since 2015
I&C Track Lead, NPIC&HMIT 2025
Student Paper Competitions Organizer and Chair, NPIC&HMIT 2023 and PSA 2023
Chair, 2023 ANS Young Professional Thermal Hydraulics Research Competition
Member, OECD Nuclear Energy Agency AI & ML Task Force (2022-present)
Panel Session Organizer and Chair, ATH 2022
Honors and Awards Chair, ANS Young Members Group (2022-2023)
Judge for best paper awards and competitions at international & national conferences (2021-present)
Member, ANS Scholarship Policy and Coordination Committee (2021-present)
Executive Committee Member, ANS Oak Ridge–Knoxville Section (2021-2023)
Guest Associate Editor, Frontiers in Energy Research (2020-present)
Research Committee Chair, Oak Ridge Postdoctoral Association (2020-2021)
Session Chair for technical sessions at international & national conferences (2017-present)
Awards and Recognitions
- Winner (mentor), Small Modular Reactor Workshop Pitch Competition, OECD Nuclear Energy Agency & Idaho National Laboratory (2023)
- Judges' Award, "Your Science in a Nutshell" Research Talk Competition, Oak Ridge National Laboratory (2022)
- Winner, ANS Human Factors, Instrumentation, and Controls Division Video Contest (2022)
- Winner, ANS Young Professional Thermal Hydraulics Research Competition (2018)
Publications
To view a complete list of Zhao's publications, view his Google Scholar profile.
Selected work:
- Zhao, X., Wang, X., and Golay, M. (2023). Bayesian Network–Based Fault Diagnostic System for Nuclear Power Plant Assets. Nuclear Technology, 209:401–418.
- Salko, R.K., Wysocki, A., Blyth, T., Toptan, A., Hu, J., Kumar, V., Dances, C., Dawn, W., Sung, Y., Kucukboyaci, V., Gurecky, W., Lange, T., Zhao, X. et al. (2022). CTF: A Modernized, Production-Level, Thermal Hydraulic Solver for the Solution of Industry-Relevant Challenge Problems in Pressurized Water Reactors. Nuclear Engineering and Design, 397:111927.
- Zhao, X., Huning, A.J., Burek, J., Guo, F., Kropaczek, D.J., and Pointer, W.D. (2022). The Pursuit of Net-Positive Sustainability for Industrial Decarbonization with Hybrid Energy Systems. Journal of Cleaner Production, 362:132349.
- Kim, J., Zhao, X., Shah, A., and Kang, H.G. (2021). System Risk Quantification and Decision Making Support Using Functional Modeling and Dynamic Bayesian Network. Reliability Engineering & System Safety, 215:107880.
- Zhao, X., Kim, J., Warns, K., Wang, X., Ramuhalli, P., Cetiner, S., Kang, H.G., and Golay, M. (2021). Prognostics and Health Management in Nuclear Power Plants: An Updated Method-Centric Review with Special Focus on Data-Driven Methods. Frontiers in Energy Research, 9:696785.
- Zhao, X., Salko, R.K., and Shirvan, K. (2021). Improved Departure from Nucleate Boiling Prediction in Rod Bundles Using a Physics-Informed Machine Learning-Aided Framework. Nuclear Engineering and Design, 374:111084.
- Zhao, X., Shirvan, K., Salko, R.K., and Guo, F. (2020). On the Prediction of Critical Heat Flux Using a Physics-Informed Machine Learning-Aided Framework. Applied Thermal Engineering, 164:114540.
- Zhao, X., Wysocki, A., Shirvan, K., and Salko, R.K. (2019). Assessment of the Subchannel Code CTF for Single- and Two-Phase Flows. Nuclear Technology, 205:338–351.
- Zhao, X., Shirvan, K., Wu, Y., and Kazimi, M.S. (2016). Critical Power and Void Fraction Prediction of Tight Bundle Designs. Nuclear Technology, 196:553–567.