Project Grant 2553935
- Federal Grant Award Summary The University of New Mexico received a $225,000 Project Grant from the National Science Foundation's Directorate for Engineering (CFDA 47.041), effective October 1, 2026 through September 30, 2029, to develop a Smart Event-Based Spectral Imager (SEBI) system that addresses data compression and classification challenges in hyperspectral imaging. The project delivers three primary technical products: (1) a configurable smart spectral imaging system with advanced...
- Federal Grant Award Summary Marquette University received a $189,426 Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective July 1, 2025, through June 30, 2027. This collaborative research initiative focuses on designing and implementing novel computational methods that leverage SmartSSD (computational storage) devices to optimize large-scale similarity and...
- Federal Project Grant Award Summary The University of Michigan received a $644,407 Project Grant award from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), effective October 15, 2025, with completion targeted for September 30, 2028. The award supports the development of an ultra-compact, chip-scale spectrometer utilizing advanced machine learning techniques for spectral reconstruction. The primary...
- Federal Project Grant Award Summary The National Science Foundation's Division of Electrical, Communications and Cyber Systems awarded a $160,000 Project Grant to the Regents of the University of Minnesota (Office of Sponsored Projects Administration) under the Engineering program (CFDA 47.041), effective September 1, 2025, through August 31, 2028. This collaborative research project develops analytical and computational methods to establish theoretical and algorithmic foundations for...
- Federal Project Grant Award Summary Michigan State University received a $400,000 Project Grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), awarded September 1, 2025, through August 31, 2028. The project develops advanced data-driven computational methods for tomographic imaging reconstruction and acquisition in extremely limited and scatter-corrupted measurement environments. The research integrates...
- Federal Project Grant Award Summary Rochester Institute of Technology received a $200,000 Engineering Research Initiation (ERI) grant from the National Science Foundation's Division of Electrical, Communications and Cyber Systems (CFDA 47.041) awarded October 1, 2025, with completion targeted for September 30, 2027. The project develops a bilevel optimization framework to model and study uncertainties in snapshot compressive imaging (SCI) systems that integrate optical hardware encoders with...
- Federal Project Grant Award Summary Missouri University of Science & Technology received a $255,707 Project Grant award from the National Science Foundation's Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), with an award date of October 15, 2025, and completion date of September 30, 2028. This collaborative research project develops a 2D chiral fingerprint metasensor system empowered by machine learning algorithms to enable...
- Federal Project Grant Award Summary The University of Michigan received a $482,504 Project Grant award from the National Science Foundation's (NSF) Directorate for Engineering (CFDA 47.041) effective September 1, 2026, through August 31, 2029. The award funds research in super-resolution acoustic diagnostics through dynamic wavelength down-conversion, a novel approach that converts acoustic signals into coherent fields with shorter wavelengths to produce high-resolution imaging comparable to...
- Federal Project Grant Award Summary Emory University's Office of Sponsored Programs received a $399,930 Project Grant award, effective September 1, 2026, through August 31, 2029, from the National Science Foundation (NSF) Division of Chemical, Bioengineering, Environmental, and Transport Systems under the Engineering program (CFDA 47.041). The project develops a plasmonic biosensing platform that converts optical measurements into direct electrical signals through quantum tunneling current...
- The National Science Foundation awarded Marquette University a $173,184 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) for the period of June 1, 2022 through May 31, 2024. The grant funds research to develop Coordinate-Based Neural Networks (CBNNs) for improving the accuracy of computational imaging techniques used in applications across science and engineering. Specifically, the University will conduct work to establish a sampling theory for...
Marquette University received a $288,964 Project Grant from the National Science Foundation's Directorate for Engineering (CFDA 47.041) awarded October 1, 2026, with completion targeted for September 30, 2029. The award supports collaborative research to develop a Smart Event-Based Spectral Imager (SEBI)—a configurable hardware-software co-design solution that addresses the data volume challenges inherent in modern hyperspectral imaging systems. The project delivers three primary technical products: (1) an advanced SEBI prototype featuring sensing algorithms that generate application-specific control signals to an electrically-tunable spectral filter, enabling selective sensing of relevant spectral and spatial information; (2) intelligent analog readout integrated circuits (IROICs) tightly coupled with the tunable filter to enable on-chip implementation of sensing algorithms; and (3) optimized machine learning models deployed on edge devices integrated with the IROIC circuitry. By transmitting only processed event outcomes rather than raw sensor data, the SEBI solution significantly reduces communication bandwidth, latency, power consumption, and data storage requirements while improving processing speed and system privacy. This approach addresses a critical gap in hyperspectral imaging technology by enabling near-sensor data processing and compression without sacrificing decision-making quality, thereby providing practical solutions for real-time spectral imaging applications requiring efficient information extraction from large-scale datasets.Federal Project Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $289.0k | 7/14/26 |