Research Areas Statistics Machine learning Nonparametric Bayes Reinforcement learning clinical trial designs Infectious disease (e.g., HIV) Electronic health/medical data.

Yanxun Xu is an associate professor of applied mathematics and statistics and an adjunct assistant professor in the Division of Biostatistics and Bioinformatics at The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins School of Medicine. She is known for developing Bayesian statistical theory and methodology for complex, heterogeneous, and large-scale datasets, with applications in a broad range of fields, such as electronic health/medical record data, cancer genomics, clinical trials, and network data. By developing novel statistical methods and new computational algorithms with open-source software, her work has led to a better understanding of heterogeneity in treatment effects across patient subpopulations in clinical trials, advanced personalized treatment response from electronic health/medical record data to facilitate precision medicine, and shed light on the effects of antiretroviral drugs on mental health and central nervous systems in HIV patients.

Xu’s research has been funded by National Science Foundation (NSF), National Institutes of Health (NIH), The Johns Hopkins Center for AIDS Research, France’s Institut National du Cancer, and various industries (e.g., AstraZeneca, Booz Allen Hamilton). She has published more than 80 articles in academic journals and co-authored three book chapters. She is the recipient of a 2016 Mitchell Prize from the International Society for Bayesian Analysis (ISBA), JHU’s Center for AIDS Research Faculty Development Award, and Hopkin’s in Health Discovery Program Award.