Jill S. Barnholtz-Sloan, Ph.D.
Associate Director for Informatics and Data Science Program
- Center for Biomedical Informatics & Information Technology
- Informatics and Data Science Program
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Current Role
Current Role
As the Associate Director for Informatics and Data Science Program, I lead efforts at CBIIT to shape informatics and data science strategies and foster collaboration within NCI and across NIH and the cancer research community. Additionally, I am pursuing a robust research agenda in descriptive epidemiology and etiology of brain tumors as an intramural senior investigator in NCI’s Division of Cancer Epidemiology and Genetics (DCEG) Trans-Divisional Research Program. Thus, as both an active researcher and administrator, I have insight into how data can be translated into real-world solutions to help diagnose, prevent, and treat cancer.
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Projects
Projects
Childhood Cancer Data Initiative (CCDI)
Develops means to collect and share childhood cancer data to learn from every child with cancer.
NCI Cancer Research Data Commons (CRDC)
Connects researchers with data sets and tools to analyze large- scale cancer research data in the cloud. -
Publications
Publications
Featured Publications
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In the News
In the News
Federated learning (FL) might well be the next paradigm shift in democratizing vast amounts of data from many data sources for use in cancer research. FL offers a decentralized, but collective, approach to using data to better understand cancer.To celebrate the “International Day of Women and Girls in Science,” we asked CBIIT’s Associate Director for Informatics and Data Science, Dr. Jill Barnholtz-Sloan, to share her experience as a woman in data science. She tells about her journey to CBIIT and underscores the value of adding women’s perspectives to the data science field.Dr. Jill Barnholtz-Sloan, CBIIT’s associate director of Informatics and Data Science and DCEG senior investigator, together with research colleagues, used a direct data matching approach to compare brain tumors in U.S. Veteran and non-Veteran populations. The study indicates that direct and deterministic data matching approaches have the potential to compare the distribution of tumors, treatment trajectories, and clinical outcomes of other cancers and rare diseases among these populations. -
Background
Background
Education
- Ph.D., Biostatistics, The University of Texas Health Science Center at Houston (UTHealth) School of Public Health
- M.S., Statistics, The University of Texas at Austin
- B.S., Mathematics, University of Florida
Previous Work
- Professor and Associate Director for Translational Informatics/Data Sciences, Case Western Reserve University School of Medicine and Case Comprehensive Cancer Center
- Director of Research Health Analytics and Informatics, University Hospitals
- Assistant Professor, Moffitt Cancer Center
- Assistant Professor, Wayne State University School of Medicine
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My Team
My Team