This Project Grant award from the National Science Foundation's (CFDA 47.049 - Mathematical and Physical Sciences) program provides $300,000.00 in funding to Purdue University to conduct research on nonlinear inverse problems. The key focus areas include: Recovery of Lorentzian metrics from measurements of light or particle propagation on a timelike boundary, with applications to cosmology and probing moving media. Recovery of Riemannian geometry from the areas of minimal surfaces on a bounded...
Purdue University received a $270,000 Project Grant award from the National Science Foundation Division of Mathematical Sciences on September 1, 2021 to complete the project by August 31, 2024. The grant supports work to integrate randomized methods and fast and reliable matrix computations under the Mathematical and Physical Sciences program (CFDA 47.049). This program aims to promote progress in mathematical and physical sciences to strengthen the national scientific enterprise and increase...
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...
Purdue University was awarded a $350,000 Project Grant from the National Science Foundation Division of Mathematical Sciences. The grant is part of the NSF's Mathematical and Physical Sciences program (CFDA 47.049) and will support research on D-modules and commutative algebra from July 1, 2021 to June 30, 2024. The funding will allow Purdue researchers to advance the store of scientific knowledge and enhance understanding of major problems in mathematics through their work developing new...
The National Science Foundation Division of Mathematical Sciences awarded a $190,838 project grant to Purdue University on July 15, 2021 with a completion date of June 30, 2024. The grant supports research titled "NEW SAMPLING ALGORITHMS AND INVERSE SPECTRAL METHODS IN SCATTERING" under the Mathematical and Physical Sciences program (CFDA 47.049). This project aims to develop new sampling algorithms and inverse spectral methods for scattering problems. The Mathematical and Physical...
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...
Purdue University was awarded a $243,904 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant will support research into algebraic structures in topology and geometry from July 1, 2021 to June 30, 2024. As part of the Mathematical and Physical Sciences program's goal of strengthening the nation's scientific enterprise through foundational work in mathematics, this...
Purdue University received a $250,000 Project Grant award from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) for the period September 1, 2023 through August 31, 2026. The award will support research at the intersection of representation theory, integrable systems, mathematical physics, combinatorics, and enumerative algebraic geometry. Specifically, the Principal Investigator will pursue five...
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 $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...