Project Grant 2410699
- 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 $300,000 Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program aims to develop novel computational methods and algorithms to recover signals from highly corrupted and distorted data. The key products and services to be delivered include: Advancing robust mathematical theory and algorithms to enable effective extraction and analysis of information from modern imaging data, such as that collected through cryo-electron...
- This federal Project Grant award of $124,487 from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) is supporting collaborative research to develop advanced statistical methods and algorithms for analyzing large-scale biomedical imaging data. The research aims to address critical challenges in causal learning and population heterogeneity when working with complex functional data, such as medical imaging outcomes. The project will create new...
- This National Science Foundation (NSF) Project Grant award, provided under the Engineering program (CFDA 47.041), is funding a collaborative research effort to develop a modeling framework that integrates limited radio measurements with spatial priors derived from environmental sensing. The $200,000 award, effective from Sep 1, 2025 to Aug 31, 2028, will support research at Virginia Polytechnic Institute & State University (Virginia Tech) to investigate how geometric and visual information...
- The National Science Foundation (NSF) awarded a Project Grant of $270,000.00 to Virginia Polytechnic Institute & State University (Virginia Tech) under the Mathematical and Physical Sciences Grant Program (CFDA 47.049) with a start date of September 1, 2025 and an end date of August 31, 2030. The overarching goal of this project is to develop new scalable Bayesian statistical methods that incorporate heavy-tailed prior distributions to address significant challenges in independent...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $125,667 Project Grant to Virginia Polytechnic Institute & State University (Virginia Tech) under the Mathematical and Physical Sciences program (CFDA 47.049). The grant will fund collaborative research to develop new theories and methodologies for multiple hypothesis testing on regression analysis, which is critical for analyzing high-dimensional data in the era of big data. The research project will create...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will investigate methods to reconstruct high-resolution discrete images from low-frequency Fourier data. The $250,000 award to Oberlin College will focus on developing new algorithms that leverage prior mathematical information about the image content to improve the quality and resolution of imaging techniques across scientific, medical, and security applications. A...
- The National Science Foundation (NSF) awarded a $200,000 Project Grant under the Engineering program (CFDA 47.041) to the Rochester Institute of Technology (RIT) to develop a new uncertainty modeling framework for snapshot compressive imaging (SCI) systems. The research aims to enhance the reliability and robustness of SCI technology, which has applications in computational imaging, signal processing, remote sensing, AI photonics, and machine learning. The project will establish computational...
- This $195,605 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop innovative frameworks for constructing advanced data compression and communication algorithms. The University of Texas at Austin is the awardee and will integrate insights from information theory, generative models, and deep learning to establish new methodologies that can drive the discovery of more efficient...
- This National Science Foundation (NSF) Division of Mathematical Sciences grant award to Drexel University provides $270,000 over three years to develop new data-driven inversion methods and image reconstruction algorithms for nonlinear media with applications in radar, medical imaging, and optical design. The key innovations include using data to generate compact wave propagation models for efficient image reconstruction, expanding the applicability to large and noisy data sets, and developing...
This $162,490 federal Project Grant awarded by the National Science Foundation's (NSF) Division of Mathematical Sciences will fund collaborative research at Virginia Polytechnic Institute & State University (Virginia Tech) to develop advanced, memory-efficient algorithms and solvers for high-dimensional imaging applications such as medical imaging and video compression. The project aims to achieve significant improvements over existing state-of-the-art methods by leveraging data properties and solution features to accelerate iterative reconstruction and compression techniques while respecting memory constraints. The research will have broad scientific impact, potentially enhancing tissue anomaly detection in medical scans and enabling more efficient compression of multi-dimensional data in fields like satellite imaging and biology. The project will also provide graduate student training. Work under this 3-year award is expected to commence on July 1, 2024.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $162.5k | 5/30/24 |