Xiao Wang, Ph.D
Research Staff Scientist, Oak Ridge National Laboratory
Joint Faculty, Data Science & Engineering Program, University of Tennessee Knoxville
Dr. Xiao Wang is a Research Staff Scientist in the Computational Science and Engineering Division at Oak Ridge National Laboratory (ORNL) and a faculty member in the Data Science and Engineering Program at the University of Tennessee, Knoxville (UTK) with additional appointment in Computer Science Department. His research lies at the intersection of artificial intelligence (AI), high-performance computing (HPC), and computational imaging.
Dr. Wang develops scalable AI algorithms, foundation models, and physics-informed learning methods that enable scientific discovery from large-scale imaging and spatiotemporal data. His work integrates AI, imaging physics, and exascale computing to reconstruct, predict, and analyze phenomena beyond the limits of conventional sensing systems. His research spans computational imaging, scientific machine learning, foundation models, inverse problems, and large-scale scientific data analysis, with applications in medical imaging, climate science, remote sensing, microscopy, astronomy, materials science, and national security.
A central theme of his research is enabling scientists to see beyond instrument limits—using scalable AI and HPC to achieve unprecedented resolution, fidelity, speed, and predictive capability in scientific observations. His research team develops next-generation AI systems capable of learning from multimodal scientific data and operating efficiently on leadership-class supercomputers.
Prior to joining ORNL, Dr. Wang received his B.S. degrees in Mathematics and Computer Science from Saint John's University and his M.S. and Ph.D. in Electrical and Computer Engineering from Purdue University, where he was advised by Dr. Charles Bouman and Dr. Samuel Midkiff. He subsequently completed postdoctoral training at Harvard Medical School and Boston Children's Hospital, focusing on advanced medical imaging and image reconstruction and mentored by Simon Warfield.
Dr. Wang has received several recognitions for his contributions to computational imaging, scientific AI, and high-performance computing, including winning the SC25 Best Paper Award, 2025 ORNL Computing and Computational Sciences Directorate Distinguished Researcher Award, the 2024 HPCwire Top Supercomputing Achievement Award, the 2022 AAPM Low-Dose CT Grand Challenge, and the 2018 Pediatric Radiology Young Investigator Award. He was also a finalist for the ACM Gordon Bell Prize in 2025, 2024, and 2017 for his work in large-scale computational imaging and earth system modeling.
Research Interests:
Artificial Intelligence, Efficient AI High-Performance Computing, Computational Imaging, Spatiotemporal Data Analysis
Education & Training
Postdoc Training in Radiology, Harvard Medical School, 2021
Ph.D. in Electrical and Computer Engineering, Purdue University, 2017
M.S.E.E. in Electrical and Computer Engineering, Purdue University, 2016
B.A. in Mathematics, St. John's University (MN), 2012
B.A. in Computer Science, St. John's University (MN), 2012
Professional Experiences
2021-- Now: Research Scientist, Computational Science & Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN
2024-- Now: Joint Appointment Assistant Professor, Data Science & Engineering Program, University of Tennessee Knoxville, Knoxville, TN
2025-- Now: Adjunct Faculty, Electrical Engineering and Computer Science , University of Tennessee Knoxville, Knoxville, TN
2017 -- 2021: Postdoctoral Research Associate, Harvard Medical School, Boston, MA
2017 -- 2021: Postdoctoral Research Associate, Boston Children's Hospital, Boston, MA
2012 -- 2017: Graduate Research Assistant, ECE, Purdue University, West Lafayette, IN
