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Yuan Ji is a Professor at the University of Chicago specializing in Bayesian statistical methods and their applications in clinical trials and precision medicine. He leads a research group focused on innovative design and analysis strategies to tackle complex cancer genomics challenges. His work involves developing novel Bayesian frameworks and statistical tools to optimize study designs in oncology. Dr. Ji has authored numerous publications in high-impact journals, addressing critical issues in cancer biology, including clonal mutation status and adaptive trial designs. He was recognized as an elected fellow of the American Statistical Association in 2020, affirming his contributions to the field. His lab encompasses a diverse team dedicated to the integration of computational methods in cancer research, emphasizing the usage of Bayesian adaptive designs that leverage real-world data to enhance treatment efficacy and patient outcomes. Guided by rigorous statistical principles, Dr. Ji's research is characterized by its applicability to ongoing clinical challenges, making significant strides in understanding tumor heterogeneity and improving therapeutic strategies.
University of Chicago • Chicago, IL
Leading research in Bayesian methods and clinical trial designs.
Department of Philosophy