Emily Greenspan, Ph.D.
Health Science Administrator
I am a Biomedical Informatics Program Director in CBIIT and serve as the NCI federal program lead for the NCI-Department of Energy (DOE) Collaboration, which applies artificial intelligence (AI) approaches and advanced computing to specific areas of cancer research. The NCI-DOE Collaboration encompasses three distinct predictive oncology projects, ADMIRRAL, MOSSAIC and IMPROVE, as well as the Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium. I also lead and support computational modeling projects and activities across NCI and NIH, including the CBIIT AI and High Performance Computing Working Group, the trans-NCI AI Working Group, and the NIH Bridge2AI Program.
Accelerating Therapeutics for Opportunities in Medicine (ATOM)Transforms drug discovery through AI, HPC, and emerging biotechnologies.
NCI-DOE CollaborationsUses advanced computation, predictive models, AI/ML to accelerate precision oncology.
Predictive Radiation Oncology – A New NCI-DOE Scientific Space and Community. Radiation Research, 2022.
Digital Twins for Predictive Oncology Will Be a Paradigm Shift for Precision Cancer Care. Nature Medicine, 2021.
AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing. Frontiers in Oncology, 2019.
In the News
In the NewsCollaboration, cooperation, and the need for multimodal, multiscale data were central themes in a recent article on NCI’s efforts to develop a cancer research digital twin.Deadline Extended: Submit Abstracts for the Eighth Computational Approaches for Cancer Workshop by August 16As the necessity for and availability of large data sets in cancer applications grows, so do the challenges when conducting research and clinical applications with computational solutions. Share your experience with how to address such challenges.Drs. Emily Greenspan and Eric Stahlberg of NCI’s CBIIT and Frederick National Laboratory for Cancer Research, respectively, recently contributed to an article, “Digital twins for predictive oncology will be a paradigm shift for precision cancer care,” published in Nature Medicine. The commentary examines the vision that members of NCI’s Envisioning Computational Innovations for Cancer Challenges (ECCIC) community have for developing cancer patient digital twins. Such a platform could revolutionize how clinicians and policymakers approach cancer care and further advance precision medicine.
- Ph.D., Biomedical Sciences, University of Connecticut Health Center
- B.A., Biochemistry, Wellesley College
- Program Director, NCI Center for Strategic Scientific Initiatives (CSSI) and the Provocative Questions Initiative
- Postdoctoral Fellow, Lombardi Comprehensive Cancer Center, Georgetown University