Project Grant 2205043
Award Date
9/1/22
Completion Date
8/31/26
Dollars Obligated
$696K
Funding Federal Agency
National Science Foundation
Awarding Federal Agency
Division of Information and Intelligent Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Alafaya, FL 32816, USA
Similar Awards
This Project Grant from the National Science Foundation Division of Computing and Communication Foundations, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $453,666 to the Palo Alto Veterans Institute For Research (Pavir) from September 1, 2022 to August 31, 2026. The funding supports research to develop a new method for quantifying cardiac performance in patients with cardiac disease by measuring myofiber strain using routinely...
This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $439,954 to Michigan State University (MSU) to develop advanced computational models of the heart that leverage machine learning and artificial intelligence. The goal is to create a multiscale modeling framework that can predict structural and functional changes in the heart due to disease conditions like pathological fibrosis. The...
This $760,046 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a computationally-efficient multiscale modeling framework that integrates machine learning and artificial intelligence to predict structural and functional changes in the heart due to disease progression. The project aims to build fundamental understanding of heart disease by combining techniques from...
The National Science Foundation awarded a $279,606 Project Grant to the University of California Irvine under the Engineering federal grant program (CFDA 47.041). The grant supports collaborative research to develop multiscale computational models characterizing how heart muscle cells adapt mechanically to changes in load conditions. Through experimental measurement and multi-scale modeling, the university researchers will elucidate the acute functional response and long-term remodeling response...
This National Science Foundation (NSF) Engineering (CFDA 47.041) program grant, in the amount of $400,000, supports the development of a tissue-like, converged sensing platform for tracking excitation-contraction dynamics in cardiac organoids. The project aims to: Develop a scalable assembly strategy to fabricate an array of three-dimensional sensor structures using planar semiconducting graphene material, designed to detect both electrical and mechanical stimuli. Evaluate the multifunctional...
The National Science Foundation awarded a $542,441 Project Grant to the Texas A&M Engineering Experiment Station to develop a validated hybrid echocardiography-computational fluid dynamics framework for patient-specific cardiac assessment under the Engineering (47.041) federal grant program. The project aims to create a computational pipeline using standard echocardiography scans to model cardiac flow and function, and compute in vivo mechanical and electrophysiological properties for...
This $262,138 Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) supports research at the University of Houston to investigate the mechanisms of cardiac fibrosis, a type of scarring in the heart that leads to impaired function. The key objectives are to: 1) determine the role of the endothelial-mesenchymal transition in cardiac fibrosis, and 2) develop a 3D cardiac fibrosis model to study tissue remodeling. The research will leverage a...
The National Science Foundation (NSF) awarded a 3-year, $567,284 Project Grant under the Engineering program (CFDA 47.041) to Purdue University to develop a scalable Bayesian methodology for reconstructing cardiovascular hemodynamic flow fields and cardiac structure from advanced medical imaging modalities like phase-contrast MRI, 4D flow MRI, and color Doppler echocardiography. The research aims to overcome limitations in current imaging techniques, such as inaccurate velocity flow...
This $200,000 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund the development of advanced computational methods to create high-fidelity, fast-running digital twins of patient hearts and cardiovascular medical devices. The project aims to deliver: 1) novel machine learning algorithms for accurate digital twin geometry reconstruction from 3D medical images, 2) an efficient inverse method to identify in vivo...
This four-year, $1.1 million Project Grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of physics-informed machine learning techniques to analyze dynamic blood flow from static subtraction computed tomographic angiography imaging. The University of Wisconsin-Milwaukee will train graduate students in deep learning methods and engage undergraduates and local high school students, particularly those from...