Project: Privacy-Preserving Federated Learning for Science
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Abstract
This repository is part of a U.S. Department of Energy (DOE) Advanced Scientific Computing Research (ASCR) project focused on developing privacy-preserving federated learning approaches for scientific foundation models. The project aims to advance secure, trustworthy, and sustainable machine learning methodologies for large-scale scientific applications. ORNL Principal Investigator: Olivera Kotevska, PhD. Project Duration: 2024-2027 Website: https://github.com/ORNL/Sci_PPFL_FM
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View paper (DOI)Open access versionOpenAlexZenodo (CERN European Organization for Nuclear Research)Published 2026-10-11
Authors: Olivera Kotevska
Institutions: University of Tennessee at Knoxville, Oak Ridge National Laboratory