NSF award 2615342 · University of Connecticut

Feedback, Learning, and Robustness in Recurrent Neural Networks: Implications for Human and Artificial Intelligence

Final report due

29 December 2029

in 1,168 days · The award ends on 31 August 2029.

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Decide about an extension3 May 2029in 928 days
award ending 2029-08-31 · Research.gov
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Extension request17 Jul 2029in 1003 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Aug 2029in 1038 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Dec 2029in 1168 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Dec 2029in 1168 days
award ending 2029-08-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Dec 2029in 1168 days
award ending 2029-08-31 · 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 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 December 2029.

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Award card

Award number: 2615342
Period of support: 1 Sep 2026 – 31 Aug 2029
Amount: $723,850
Awardee: University of Connecticut, Storrs, CT
Program: Cross-Directorate Activities
Directorate: SBE

Abstract

A key ingredient in intelligent perception of the world is predictive processing: combining what the senses take in with what a person already knows and expects. As someone listens, the topic, the surrounding words, and knowledge of language help predict what is coming next. This is part of why speech can still be perceived in a noisy room, where much of the sound reaching the ear is muffled or even missing.…

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