Xingang Zhao is joining the Department of Nuclear Engineering this fall as an assistant professor.
Zhao comes to UT from Oak Ridge National Laboratory (ORNL), where he spent four years working in the Nuclear Energy and Fuel Cycle Division. He received his master’s and PhD degrees in nuclear science and engineering from the Massachusetts Institute of Technology (MIT).
Zhao has authored over 50 publications and led or contributed to six successful research grants, securing $10 million in funding mostly from the U.S. Department of Energy.
Zhao’s Research Efforts
Zhao’s research interests span multiple disciplines of nuclear energy systems—with an emphasis on instrumentation and controls (I&C) and thermal hydraulics (T-H)—and their intersections with artificial intelligence (AI) and decision science.
The primary goal of Zhao’s research is to develop integrated modeling and simulation capabilities that enhance the safety and operational performance of current and future nuclear power plants. To achieve this goal, Zhao is founding the research group “X-Group” (X = crosscutting). The X-Group will harness enabling technologies in nuclear and digital engineering to accelerate the development and deployment of digital twins (DTs) and explore innovative approaches to strengthen the integration of experiments and simulations.
Looking Towards His Future Career
“A faculty position at UT is truly a dream job for me. Beyond my research interests, I have always aspired to be a dedicated educator and a caring mentor, inspired by my own advisors at MIT and ORNL,” Zhao said. “I understand that the faculty journey may be challenging at times, but it is incredibly rewarding to contribute to the development of the next generation of nuclear engineers and scientists. I look forward to continuing my growth alongside students and peers at UT.
Zhao received the 2024 American Nuclear Society (ANS) Ted Quinn Early Career Award for his role in developing and integrating I&C and human-machine interface technologies, including DT, AI, decision science, and prognostics and health management, to enhance nuclear plant safety and efficiency. He also won the ANS Young Professional T-H Research Competition for his pioneering work in applying physics-informed machine learning to nuclear engineering, potentially improving the industry’s economic competitiveness.
“I hope to make this new chapter of my career one that is student-first,” Zhao said. “The success of my graduate and undergraduate students in their education and research will be my greatest achievement at UT.”
Contact
Rhiannon Potkey (865-974-0683, rpotkey@utk.edu)