Rate My Professor Xuan Wang

Xuan Wang is an Assistant Professor in the Division of Biostatistics within the Department of Population Health Sciences at the University of Utah School of Medicine. She earned her Bachelor of Science degree from Beijing Jiaotong University and her PhD from the Academy of Mathematics and Systems Science of the Chinese Academy of Sciences. Prior to her current appointment, she held postdoctoral fellowships at the University of Washington and Harvard University. Her career trajectory reflects a commitment to advancing biostatistical methodologies through rigorous academic training and practical application in health sciences research.

Wang's research specializations include statistical methods for surrogate validation, causal inference and missing data analysis, complex survival data analysis, supervised learning, semi-supervised learning, and federated transfer learning. She focuses on applying these novel statistical approaches to real-world data, particularly electronic health records (EHR) to enhance risk prediction and clinical decision-making. Key publications demonstrate her contributions to the field. In 2023, she co-authored 'Quantifying and Interpreting the Prediction Accuracy of Models for the Time of a Cardiovascular Event-Moving Beyond C Statistic: A Review' in JAMA Cardiology. That same year, 'Risk prediction with imperfect survival outcome information from electronic health records' appeared in Biometrics. In 2022, 'SurvMaximin: Robust federated approach to transporting survival risk prediction models' was published in the Journal of Biomedical Informatics. Additional notable works include 'Endovascular Aneurysm Repair Devices as a Use Case for Postmarketing Surveillance of Medical Devices' in JAMA Internal Medicine (2023) and 'Semiparametric Joint Modeling to Estimate the Treatment Effect on a Longitudinal Surrogate with Missing Data' forthcoming in Biometrics (2025). With 48 selected publications, her work underscores advancements in biostatistics for population health sciences.