Project Grant 2629806
Award Date 8/1/26
Completion Date 7/31/27
Dollars Obligated $145K
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Kennesaw, GA 30144, USA
Similar Awards
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Kansas Center For Research Inc. $385,250 on June 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop an integrated machine learning framework for analyzing longitudinal healthcare data. The research spans three complementary activities. The team will design deep learning architectures that jointly model patient visit sequences and...
- Federal Grant Award Summary The National Science Foundation's Division of Electrical, Communications and Cyber Systems awarded a $199,829 Engineering Research Initiation (ERI) Project Grant to Kennesaw State University Research and Service Foundation, Inc. on October 1, 2025, with completion scheduled for September 30, 2027. This project delivers fundamental research and development outputs focused on federated spiking neural networks (SNNs) optimized for distributed learning in wireless edge...
- This $170,000 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop robust and human-aligned deep learning techniques for analyzing medical sensor time-series data. The primary goals are to: 1) identify input confounders that lead to spurious correlations in time-series data, 2) design knowledge-editing strategies to correct these spurious correlations, and 3) investigate the techniques...
- The National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems awarded the University of Georgia Research Foundation $546,167 on June 1, 2026, under the NSF Engineering CAREER program (CFDA 47.041) to develop an artificial intelligence framework for integrating multimodal biomedical data to advance personalized disease monitoring and treatment of neurological conditions. The award funds development of a unified AI-driven system combining machine...
- The National Science Foundation awarded Cardiophi LLC $532,000 under the Technology, Innovation, and Partnerships program to develop an artificial intelligence solution for the automated interpretation of electrocardiograms. The project aims to refine existing deep learning-based algorithms for detecting irregular heartbeats, develop methods for predicting the onset of cardiac arrhythmias, and create interpretable and explainable tools to provide insights from ECG signals to clinicians....
- 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 Regents of the University of Minnesota received a $122,214 Computer and Information Science and Engineering (CFDA 47.070) project grant from the National Science Foundation (NSF). The grant will fund the development of a machine learning-based clinical decision support framework to assist epileptologists in diagnosing epilepsy. The key products and services to be delivered include: A fully automated and efficient electroencephalography (EEG) data preprocessing pipeline using deep learning...
- The National Science Foundation (NSF) awarded a $275,000 Phase I Small Business Innovation Research (SBIR) grant under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program to KAI TECH LLC. The funding supports the development of an advanced software system called ECG-AID for automated electrocardiogram (ECG) analysis and interpretation. The ECG-AID prototype integrates a comprehensive ECG database, Z-score-based assessments, and machine-learning techniques to enhance the...
- 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...
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $298,450 Project Grant on January 1, 2024 to the Georgia State University Research Foundation Inc., a non-profit organization, under the Computer and Information Science and Engineering (CFDA 47.070) program. Through this grant, the researchers at Georgia State University aim to develop a method to identify areas in Georgia school districts that are at higher risk for lack of access to computer...