Project Grant 2501059

Award Date 9/15/25
Completion Date 8/31/29
Dollars Obligated $1M
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Charlottesville, VA, USA
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This $1,000,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports the development of generative imaging models to verify and explain machine learning systems for healthcare applications. The key goals include:

  1. Developing robust "robustness audits" using synthetic data to assess how well a healthcare deep learning system will operate at different clinical sites, given variability in imaging data and protocols.

  2. Using deep generative models to create realistic synthetic medical images that can be used to measure the robustness of deep learning healthcare systems.

  3. Designing natural language models to communicate the results of the robustness audits to clinicians in an understandable way.

The project aims to address the lack of trustworthiness in AI/deep learning healthcare systems, which is a major obstacle to their widespread clinical adoption. The award was made to the Rector & Visitors of the University of Virginia, a prominent research university, and is slated to run from September 2025 to August 2029.

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