Newswise — WASHINGTON, D.C. - Today, the U.S. Department of Energy (DOE) announced $1 million for collaborations in privacy-preserving artificial intelligence research. The aim of this funding is to bring together researchers from the DOE National Laboratories and the National Institutes of Health (NIH) to jointly develop new flagship datasets and privacy-preserving methods and algorithms to improve healthcare. This funding is in response to congressional direction for the DOE to expand its successful collaborative research efforts with NIH in the data and computational mission space.
Biomedical and behavioral researchers have collected vast amounts of data across spatial and temporal scales, including information about genetics, tissue structure and function, and the human body as a whole. This combination of massive datasets and machine learning advances makes it possible to build a bridge to improved research and health outcomes. Accordingly, the NIH Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) program was recently announced and is soliciting proposals to generate flagship datasets that can be used to address biomedical and behavioral research grand challenges via artificial intelligence and machine learning analysis through its first NIH Bridge2AI Research Opportunity Announcement.
“DOE national laboratories have world-class computing and data management resources,” said Barbara Helland, DOE Associate Director of Science for Advanced Scientific Computing Research (ASCR). “Coupling privacy-preserving artificial intelligence methods and algorithms and DOE’s high-performance computers with NIH data will accelerate biomedical research.”
The DOE announcement is soliciting laboratory-led collaborative proposals that address the important issues and challenges of artificial intelligence/machine learning analysis on privacy-sensitive datasets. The collaborative funding announcement links NIH-DOE programs under its title of “Bridge2AI and Privacy-Preserving Artificial Intelligence Research.”
Total planned funding is up to $1 million in Fiscal Year 2021 dollars for projects of one year in duration. Awards will be selected based on peer review.
The full text of the DOE Laboratory Announcement, sponsored by the Office of Advanced Scientific Computing Research within the Department’s Office of Science, can be found here.
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