NSF award 2532643 · Regents of the University of Michigan - Ann Arbor

In-Context Learning for Sim2Real Reconstructive Spectroscopy: Bridging Modern Machine Learning and Hardware-Software Co-Design

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: 2532643
Period of support: 15 Oct 2025 – 30 Sep 2028
Amount: $644,407
Awardee: Regents of the University of Michigan - Ann Arbor, ANN Arbor, MI
Program: CSCS: Circuits and Systems for
Directorate: ENG

Abstract

Optical spectroscopy plays a crucial role across various scientific fields, from chemical process analysis to material identification and fluorescence detection. Driven by the demand for portable and field-deployable tools, miniaturizing spectroscopic systems onto chip-scale platforms has become a major research focus. This project leverages cutting-edge machine learning techniques for spectral reconstruction to…

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