NSF award 2512644 · Michigan State University

Graph-based semi-supervised techniques for machine learning tasks at low label rates

Final report due

29 December 2028

in 803 days · The award ends on 31 August 2028.

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award ending 2028-08-31 · Research.gov
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PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2028in 673 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2028in 803 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2028in 803 days
award ending 2028-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2028in 803 days
award ending 2028-08-31 · 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 August 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2028.

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Award card

Award number: 2512644
Period of support: 1 Sep 2025 – 31 Aug 2028
Amount: $379,999
Awardee: Michigan State University, East Lansing, MI
Program: COMPUTATIONAL MATHEMATICS
Directorate: MPS

Abstract

Machine learning is a type of artificial intelligence that enables a machine to learn from data. The success of machine learning is dependent upon a sufficient amount of labeled data samples. A key limitation of most machine learning methods is their reliance on large labeled sets. Labeled data is scarce for many applications. Obtaining enough labeled data is often difficult because it is time-consuming and…

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