NSF award 2607344 · University of Southern California

CAREER: Dynamic Distributed Learning in Spiking Neural Networks with Neural Architecture Search

Final report due

29 April 2028

in 558 days · The award ends on 31 December 2027.

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Decide about an extension2 Sep 2027in 318 days
award ending 2027-12-31 · Research.gov
This one is ours, not NSF’s.
Extension request16 Nov 2027in 393 days
award ending 2027-12-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Dec 2027in 428 days
award ending 2027-12-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due29 Apr 2028in 558 days
award ending 2027-12-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due29 Apr 2028in 558 days
award ending 2027-12-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out29 Apr 2028in 558 days
award ending 2027-12-31 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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How we got this date

NSF lists this award's end date as 31 December 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 29 April 2028.

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Award card

Award number: 2607344
Period of support: 1 Oct 2025 – 31 Dec 2027
Amount: $504,806
Awardee: University of Southern California, LOS Angeles, CA
Program: Software & Hardware Foundation
Directorate: CSE

Abstract

Artificial Intelligence (AI) has enabled a plethora of applications today, ranging from the most recent chatbots that give you a human-like question/answer experience to autonomous driving cars. But, all these massive feats with AI incur huge costs in terms of energy, memory, and power consumption. In the past decade, Spiking Neural Networks (SNNs) have emerged as a low-power alternative to AI. SNN’s main attraction…

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