Project Grant 2409855
Award Date
7/1/24
Completion Date
6/30/27
Dollars Obligated
$275K
Federal Agency
Division of Mathematical Sciences
Federal Grant Program
47.049
Assistance Type
Project Grant
Place of Performance
Ithaca, NY, USA
Similar Awards
This $300,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports fundamental research on inverse boundary value problems and related mathematical techniques. The key research areas include: Electrical impedance tomography (EIT) for determining the conductivity of materials by making voltage and current measurements at the boundary. The research will address challenges in EIT such as partial data, anisotropic...
This National Science Foundation (NSF) Project Grant award to Rowan University, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $212,933 from September 1, 2023 to August 31, 2025 to develop and implement new robust and computationally efficient inversion algorithms for inverse medium scattering problems. The project aims to advance inverse scattering theory, which plays a key role in technologies such as medical imaging, geophysical exploration, and unexploded...
This $170,000 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences supports research on developing randomized algorithms for solving inverse problems and quantifying uncertainty in hierarchical Bayesian and dynamical inverse problems. Key goals include: (i) creating efficient algorithms to estimate uncertainty in the hyperparameters that govern Bayesian inverse problems, and (ii) developing new iterative methods leveraging randomization to...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support research focused on geometric inverse problems and dynamics. The $335,956 award to the University of Washington will center on the study of inverse problems involving transport-type partial differential equations, with applications in areas like X-ray computed tomography, geophysical prospection, and parameter identification for PDEs. The project will...
This three-year $100,000 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) will support the development of novel computational methods for large-scale inverse problems, randomized numerical linear algebra, and sparse principal component analysis at Arizona State University. The grant will advance efficient tools for solving large-scale inverse problems in scientific applications experiencing...
This $269,999 federal Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program supports research to develop novel inverse scattering techniques for complex materials with applications in areas such as renewable energy, medical diagnosis, underground exploration, infrastructure integrity, and advanced manufacturing. The primary objectives are to investigate non-iterative approaches for...
This $100,000 three-year Project Grant from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support research to advance numerical methods for large-scale inverse problems, sparse principal component analysis, and their applications. The awardee, Emory University, will collaborate with other institutions to develop novel approaches merging inverse problems, randomized numerical linear algebra, and sparse principal component analysis. This will...
This $170,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at North Carolina State University (NC State) to develop new randomized algorithms for solving large-scale inverse problems and quantifying uncertainty in hierarchical Bayesian models. The key research objectives are: (i) to create efficient algorithms for quantifying uncertainty in the hyperparameters governing Bayesian inverse...
This Project Grant from the National Science Foundation Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $162,012 to Michigan State University for research and education activities related to inverse problems for wave equations from August 1, 2023 to July 31, 2028. The award supports the development of mathematical theory and computational methods to advance non-destructive probing techniques. The grantee will investigate fundamental...
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...