Xiao Wang is a research staff scientist at Oak Ridge National Lab. He received Bachelors degrees in both Mathematics and Computer Science with honor from Saint John’s University, MN, in 2012, and Masters degree in electrical and compute engineering from Purdue University, West Lafayette, IN, in 2016. In 2017, He received a PhD degree in electrical and computer engineering from Purdue University, under the supervision of Professor Charles Bouman and Samuel Midkiff. Then, he pursued postdoctoral research training at Harvard Medical School and Boston Children's Hospital under the supervision of Professor Simon Warfield till 2021.
Xiao Wang's research interest focuses on applying machine learning, medical physics, image processing and high performance computing to all different kinds of imaging problems, such as computed tomographic (CT) reconstruction, electron tomography imaging, and Magnetic Resonance Imaging, so that the imaging algorithm tightly integrates with detector sensor design and data acquisition physics, making it possible to observe phenomena at a super-resolution previously difficult or impossible to measure with traditional approaches. In addition, he also applies high performance computing techniques to these imaging methods to achieve real-time imaging. Applications of his research work are applied to CT medical imaging, security imaging, biology microscopy imaging and synchrotron imaging. He was the 2022 AAPM Truth CT reconstruction challenge winner and was the 2017 ACM Gordon Bell Prize finalist for his research work on CT image reconstruction.