NSF award 2606084 · University of North Carolina at Chapel Hill

Structure-Informed Machine Learning: Harnessing and Extending Group Symmetries

Final report due

28 November 2029

in 1,137 days · The award ends on 31 July 2029.

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award ending 2029-07-31 · Research.gov
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Extension request16 Jun 2029in 972 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Jul 2029in 1007 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Nov 2029in 1137 days
award ending 2029-07-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 31 July 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 November 2029.

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Award card

Award number: 2606084
Period of support: 15 Aug 2026 – 31 Jul 2029
Amount: $180,000
Awardee: University of North Carolina at Chapel Hill, Chapel Hill, NC
Program: OFFICE OF MULTIDISCIPLINARY AC, APPLIED MATHEMATICS
Directorate: MPS

Abstract

The large amounts of data and computation required of modern artificial intelligence (AI) systems continues to make efficiency, reliability, and uncertainty quantification fundamental scientific challenges. This project develops new mathematical foundations for machine learning methods that incorporate intrinsic symmetries and other forms for structure found in many real-world datasets. The mathematics developed in…

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