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 under the Mathematical and Physical Sciences Program (CFDA 47.049) provides $270,000 in funding to the University of California, Santa Barbara (UCSB) from August 1, 2024 to July 31, 2027. The project aims to address theoretical and applied challenges in seismic tomography and transport theory. Key research activities include: Studying the uniqueness and stability of travel time tomography in anisotropic elasticity, as well as uncertainty...
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 $250,000 two-year Project Grant from the National Science Foundation's Mathematical and Physical Sciences Directorate (CFDA 47.049) funds research at Rochester Institute of Technology to develop direct variational methods for solving inverse problems governed by differential equation models using full-field data. Specifically, the award supports advancing the Direct Error in Constitutive Equations formulation for determining wave speed from time-harmonic wave field observations of a...
The University of California, Santa Barbara received a $280,000 Project Grant award from the National Science Foundation Division of Mathematical Sciences on August 15, 2021 to complete the project by July 31, 2024. The grant funds the "Bridging the Mathematical Analysis and Reconstruction Algorithms for Transmission and Reflection Seismic Tomography" project. This project aims to advance mathematical and algorithmic methods for seismic tomography, which is used to image the interior...
This $270,000 Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research at the University of California, Irvine (UC Irvine) to develop novel mathematical methods for investigating inverse problems related to the recovery of anisotropic medium parameters from measurements taken at the exterior or boundary. The project aims to leverage nonlocality, nonlinearity, and high frequencies as tools to tackle significant and...
This $275,000 Project Grant awarded by the National Science Foundation's (NSF) Division of Mathematical Sciences supports the development of novel approaches to solving inverse problems. The goal is to enhance the accuracy and efficiency of computational methods used in critical applications like electrical impedance tomography, inverse scattering, and cryo-electron microscopy. This research has the potential to accelerate breakthroughs in molecular biology and rapid drug development, directly...
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 $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 $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...