Feng Xie is currently a postdoctoral scholar in Aghaeepour Lab 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. During his Ph.D. study, he utilized interpretable machine learning tools in acute and emergency care settings. Specifically, he developed a novel informatics framework called AutoScore, which automatically generates interpretable clinical scores from electronic health records. This open-source software package has been used by local and international researchers, downloaded about 400 times per month from the CRAN platform. His research interests include machine learning, clinical informatics and decision-making, predictive models, electronic health records, and risk stratification in acute care settings. He is working on machine learning analysis of EHR data which a focus on Neonatal ICU. Check out more about myself and updated profile here: https://profiles.stanford.edu/299661
I am a nature explorer and love outdoor sports. I used to learn and do many water sports, including kayaking, scuba diving, free diving, sailing and surfing. I also like mountain sports such as hiking, climbing, camping and caving. Let me know if you are also interested in exploring nature through different means.