Masonic Cancer Center announces new Data Sciences leadership
The Masonic Cancer Center (MCC), University of Minnesota is pleased to announce the appointment of J. Sunil Rao, PhD, and Schelomo Marmor, PhD, MPH, as co-associate directors of Data Sciences. Justin Hwang, PhD, has also been named assistant director of Data Sciences. All three appointments took effect in April 2026.
In these new roles, the leadership team will guide MCC’s strategy for using data, analytics, informatics, and computational methods to support cancer research across the University.
Cancer research increasingly depends on the ability to organize and analyze large, complex datasets, including genomic information, electronic health records, clinical trial data, population-level information, and cancer registry data. The Data Sciences leadership team will work with MCC leadership to establish priorities for data science efforts and with researchers and institutional partners to strengthen data infrastructure. They will also help connect investigators with analytical expertise and identify opportunities for collaboration across research programs.
Rao is a professor and director of the Division of Biostatistics in the University of Minnesota School of Public Health whose expertise includes statistical methodology, machine learning, predictive modeling, and the analysis of complex biomedical data.
Marmor is a professor in the Medical School’s Division of Surgical Oncology and a health services researcher and data scientist whose research uses electronic health records, Medicare claims, cancer registries, and other large datasets to study cancer care delivery, quality, outcomes, and variation across health systems.
Hwang is an assistant professor in the Medical School’s Division of Hematology, Oncology and Transplantation whose laboratory uses genomic data, bioinformatics, and machine learning to study tumor biology and identify biomarkers, therapeutic targets, and strategies that may help improve cancer detection and treatment.
This team of faculty brings expertise spanning biostatistics, health informatics, real-world evidence, genomics, and computational research. Their leadership will help researchers make more effective use of data, strengthen connections among the many teams working in this area across the University, and shape long-term priorities for data sciences at MCC.