NSF award 2542166 · Rochester Institute of Tech

CAREER: AdaptTrust: Adaptable, Trustworthy and Uncertainty-Aware Learning in Intelligent Sensing Technologies

Final report due

29 July 2031

in 1,745 days · The award ends on 31 March 2031.

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Decide about an extension1 Dec 2030in 1505 days
award ending 2031-03-31 · Research.gov
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Extension request14 Feb 2031in 1580 days
award ending 2031-03-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Mar 2031in 1615 days
award ending 2031-03-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Jul 2031in 1745 days
award ending 2031-03-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Jul 2031in 1745 days
award ending 2031-03-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Jul 2031in 1745 days
award ending 2031-03-31 · 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 March 2031.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 July 2031.

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Award card

Award number: 2542166
Period of support: 1 Apr 2026 – 31 Mar 2031
Amount: $560,000
Awardee: Rochester Institute of Tech, Rochester, NY
Program: EPCL: Energy, Power, Control,
Directorate: ENG

Abstract

This NSF CAREER project aims to develop machine learning systems that continuously learn from new data without forgetting prior knowledge. Today’s machine learning models are powerful but largely static, often overwriting earlier information when updated, a problem known as catastrophic forgetting that reduces reliability in evolving environments, such as healthcare monitoring, environmental sensing, and autonomous…

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