NSF award 2501413 · Kennesaw State University Research and Service Foundation

ERI: Towards Efficient and Robust Federated Neuromorphic Learning in Wireless Edge Networks

Final report due

28 January 2028

in 467 days · The award ends on 30 September 2027.

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Decide about an extension2 Jun 2027in 227 days
award ending 2027-09-30 · Research.gov
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Extension request16 Aug 2027in 302 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2027in 337 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2028in 467 days
award ending 2027-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2028in 467 days
award ending 2027-09-30 · 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 30 September 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2028.

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Award card

Award number: 2501413
Period of support: 1 Oct 2025 – 30 Sep 2027
Amount: $199,829
Awardee: Kennesaw State University Research and Service Foundation, Kennesaw, GA
Program: ERI-Eng. Research Initiation
Directorate: ENG

Abstract

Current distributed learning systems predominantly rely on artificial neural networks, which are generally energy-intensive. This issue is further exacerbated with the use of more advanced and larger models. In contrast, brain-inspired neuromorphic learning algorithms, such as spiking neural networks (SNNs), are renowned for their energy efficiency, making them particularly promising for low-power edge applications.…

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