NSF award 2537086 · California Institute of Technology

Machine learning for dynamic spectrum access in passive radio sensing

Final report due

28 January 2029

in 833 days · The award ends on 30 September 2028.

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Decide about an extension2 Jun 2028in 593 days
award ending 2028-09-30 · Research.gov
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Extension request16 Aug 2028in 668 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2028in 703 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2029in 833 days
award ending 2028-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2029in 833 days
award ending 2028-09-30 · 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 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2029.

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Award card

Award number: 2537086
Period of support: 1 Oct 2025 – 30 Sep 2028
Amount: $759,977
Awardee: California Institute of Technology, Pasadena, CA
Program: SII-Spectrum Innovation Initia
Directorate: MPS

Abstract

This project develops methods and tools that use artificial intelligence and machine learning (AI/ML) to help overcome the problem of radio-frequency interference (RFI) in measurements made by radio telescopes. The techniques could benefit other sensitive receivers threatened by RFI, for example weather radars. RFI is a growing challenge for instruments like telescopes and radars due to increasing usage of the radio…

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