Yao Sui is an Assistant Professor at National Institute of Health Data Science, Peking University, with research interests in a broad range of medical and engineering disciplines, including specific expertise and research experience in neuroimaging, medical image computing, machine learning, computer vision, and artificial intelligence. The goal of his research is to advance our understanding of the structure and function of the brain for improving our capacity to diagnose and treat disease. His research to date has focused on developing novel technologies and computational image models, in order to understand and interpret radiological images. The most significant accomplishments of his research have been the development of novel paradigms and algorithms for fundamentally new approaches to analyze and interpret images. He has set up new research studies to develop cutting-edge techniques of artificial intelligence, machine learning, computer vision, and signal processing. These studies provide solid theoretical and technical bases in his research in medical imaging. Many of his algorithmic developments have introduced entirely new approaches in the field, which have been adopted by others nationally and internationally as a basis for new directions for development. These studies have resulted in 30+ peer-reviewed publications in premium journals and conferences, among which 20+ were first-authored.
He is highly motivated to develop and translate novel imaging technologies into clinical practices. Major applications have included real-time motion-robust MRI acquisition, and motion-compensated MRI reconstruction, to support image-guided surgery, fast and high-quality brain MRI, and quantitative image analysis, to detect morphological change for preoperative assessment of seizure foci and normal function in pediatric epilepsy patients.
He has successfully collaborated with multi-disciplinary research teams and industry to develop new imaging techniques and software tools. His research has been characterized by fundamental contributions to the basic science of imaging and medical image analysis, and collaboration with clinicians to translate those contributions into dramatic impact in clinical and translational research.
