Bio
Feng Xie is currently a postdoctoral scholar at Stanford University School of Medicine, and he recently graduated with a joint Ph.D. degree from Duke University and the National University of Singapore. He previously obtained his bachelor’s degree from Tsinghua University, Beijing, China, in 2017. His research focuses on developing novel informatics methodologies and applying them to various healthcare domains, including children’s health, critical care, and emergency medicine. He extensively utilized large-scale multimodal data including electronic health records (EHR), clinical notes, and medical signal data, to address critical healthcare challenges. In his Ph.D. and postdoctoral training, he developed multiple advanced methods and informatics tools, including AutoScore, MIMIC-IV-ED benchmark, and NeonatalBERT. Used by other researchers globally, some of them have been applied to a wide range of clinical applications including risk prediction and model benchmarking, resulting in dozens of publications by other users. Specifically, AutoScore software has been downloaded more than 10,000 times from the R CRAN platform. and the original paper has garnered over 70 official citations for about 2 years.
Over 5 years, he published 8 first-author research papers in high-impact journals in the field, with a total impact factor of over 60. His extensive collaborations with clinicians, engineers, and health service researchers also resulted in 12 co-author papers.
