Yuan Ji

Yuan Ji is a Professor in the Department of Public Health Sciences at the University of Chicago. Her research focuses on biostatistics, bioinformatics, and Bayesian methods applied to oncology and clinical trial design. She leads the Biostatistics and Bioinformatics Lab (BBL), which develops innovative statistical frameworks for precision medicine, tumor heterogeneity analysis, and adaptive clinical trial designs. Her work integrates multi-omics data and imaging biomarkers to improve cancer diagnosis and treatment.

Key contributions include the development of the i3+3 dose-finding design for oncology trials, Bayesian hierarchical models for tumor subclone reconstruction (Mutstats), and the TCGA-assembler software for genomic data processing. She has received the 2015 Mitchell Prize from the International Society for Bayesian Analysis and was elected a Fellow of the American Statistical Association in 2020.

Current research emphasizes integrating radiomics, genomics, and clinical data to predict treatment outcomes. Her grants include NIH R01CA132897, focusing on Bayesian inference for tumor heterogeneity using next-generation sequencing. Collaborations span cancer genomics, neurovascular disorders, and personalized therapy development.