Project Grant 2450988
- The National Science Foundation (NSF) awarded a $320,000 Project Grant under the Engineering program (CFDA 47.041) to Oregon State University (OSU) for the project "Collaborative Research: Unregistered Spectral Image Fusion in Remote Sensing: Foundations and Algorithms." The project, running from September 1, 2025 to August 31, 2028, aims to develop new analytical and computational methods to establish a theoretical and algorithmic foundation for fusing unregistered spectral data, such...
- This federal Project Grant award of $300,000 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) will support the "HS-SPECTRA" (Hyperspectral Standardizing and Sharing Possibilities for Urban Conditions through Toolkits, Resources and Archiving) project at New York University (NYU). The project aims to address fundamental challenges in hyperspectral library design for urban material identification by: 1) developing a metadata architecture for longitudinal urban...
- This federal Project Grant award of $200,000 from the National Science Foundation's Engineering program (CFDA 47.041) aims to enhance the reliability and robustness of snapshot compressive imaging (SCI) systems. The primary objective is to develop a versatile bilevel optimization framework to study uncertainties in hybrid models that combine physical optics and deep learning algorithms for SCI. The research focuses on modeling mask, weight, and data uncertainties to establish the computational...
- This federal Project Grant award of $250,000 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support research to reconstruct high-resolution images from low-frequency Fourier data. The project aims to leverage prior mathematical information to dramatically improve the resolution of images containing distinct types of materials, such as in scientific imaging, medical scans, and security screenings. The research will focus on developing...
- This $162,510 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences will fund collaborative research at Tufts University to develop innovative, memory-efficient algorithms for high-dimensional imaging applications such as medical imaging, object inspection, and video surveillance. The key products will be accelerated reconstruction and compression techniques that can process large volumes of multi-dimensional imaging data in real-time while using...
- This federal Project Grant award of $239,420.00 from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research to advance statistical methods for analyzing complex spatial data. The investigators at the Colorado School of Mines aim to develop novel frequency domain resampling techniques that can effectively handle irregularly spaced spatial data, a common challenge in fields like geosciences and environmental science. The new methods will...
- This $365,274 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of novel mathematical techniques and algorithms for designing cost-effective space-time sampling strategies and reconstruction methods for time-evolving functions on graphs. A diverse group of researchers from Northern Illinois University will work to analyze and manage various time-evolving processes sampled under realistic conditions and...
- This National Science Foundation (NSF) Engineering program (CFDA 47.041) project grant awarded $644,407 to the Regents of the University of Michigan on October 15, 2025, with a completion date of September 30, 2028. The project aims to develop an ultra-compact, chip-scale spectrometer with high reconstruction accuracy through the integrated co-design of hardware and modern machine learning algorithms. The key objectives are to: (i) develop device-informed simulation-to-real in-context learning...
- This $558,594 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The grant supports research at the University of South Florida (USF) to develop new mathematical tools and a unified framework for studying the fundamental limits of computational imaging systems. The project aims to tackle deficiencies in existing techniques for analyzing the performance and jointly optimizing the...
- This $227,796 Project Grant awarded by the National Science Foundation's (CFDA 47.049 - Mathematical and Physical Sciences) focuses on developing new mathematical techniques to more effectively analyze signals by carefully isolating their distinct parts in time, space, or frequency. The research aims to improve understanding of spatio-spectral limiting operators, which can significantly enhance everyday technologies like MRI machines, wireless communications, and scientific imaging. In...
This Project Grant award of $160,000.00 from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will support collaborative research to develop new analytical and computational methods for spectral image fusion of unregistered remote sensing data. The project aims to establish a rigorous theoretical and algorithmic foundation for integrating high-resolution hyperspectral and multispectral imagery, even when the data are spatially misaligned due to differences in sensors or imaging platforms. The research outcomes are expected to benefit remote sensing applications such as agriculture, oceanography, and space exploration, as well as other areas like medical imaging and machine learning. The award will fund this 3-year research project led by the Regents of the University of Minnesota, with the goal of enabling performance-guaranteed fusion of unregistered spectral data in real-world scenarios.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $160.0k | 8/19/25 |