Yanxun Xu

Yanxun Xu is an Associate Professor of Applied Mathematics and Statistics at the Whiting School of Engineering, Johns Hopkins University, and an Adjunct Assistant Professor in the Division of Biostatistics and Bioinformatics at the Sidney Kimmel Comprehensive Cancer Center. She is also a member of the Data Science and Artificial Intelligence Institute. Her research focuses on developing Bayesian statistical methods and machine learning algorithms to address challenges in heterogeneous, large-scale datasets, particularly in clinical trials, electronic health records, cancer genomics, and HIV/AIDS studies.

Key areas of expertise include nonparametric Bayes, reinforcement learning, and dynamic treatment regimes. Her work emphasizes precision medicine applications, such as optimizing antiretroviral therapies for HIV patients and analyzing cognitive outcomes in clinical trials. Funding sources include the National Science Foundation (NSF), National Institutes of Health (NIH), and industry partners like AstraZeneca.

Xu has published over 80 peer-reviewed articles and received prestigious awards, including the 2016 Mitchell Prize from the International Society for Bayesian Analysis. Her research bridges statistical theory with real-world healthcare applications, addressing topics like hospital-level variations in COVID-19 treatment and the impact of inflammation biomarkers on neurocognitive functions in psychosis.

• PhD in Biostatistics (implied by academic rank)
• Recipient of JHU’s Center for AIDS Research Faculty Development Award
• Developed open-source software tools for causal inference and longitudinal data analysis