The National Science Foundation (NSF) awarded a $175,000 project grant under the Mathematical and Physical Sciences (CFDA 47.049) program to Embry-Riddle Aeronautical University, Inc. The grant, effective August 1, 2024 through July 31, 2027, will support collaborative research to develop data-driven methods for realizing and predicting the behavior of state-space dynamical systems using low-complexity algorithms. The project aims to leverage advanced machine learning techniques to efficiently...
This $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of next-generation mathematical and algorithmic tools to address two key issues in applying machine learning to statistical modeling of time-evolving complex systems: a shortage of informative training data and the high computational costs of high-dimensional problems. Specifically, the...
The National Science Foundation awarded a $152,899 Project Grant to Florida State University (FSU) under the Mathematical and Physical Sciences (CFDA 47.049) program. This grant supports research into stochastic analysis and numerical algorithms for stochastic dynamical systems, and their applications in machine learning and mathematical finance. Key focus areas include hypocoercivity and convergence analysis for degenerate and mean-field stochastic systems, and the study of non-Markovian...
The National Science Foundation awarded Florida State University a $163,533 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) from July 1, 2022 to June 30, 2025. The award will support research developing a theoretical framework to better understand how heavy-tailed distributions arise in popular machine learning algorithms and how they can explain the success of these algorithms. The awardee will conduct research obtaining theoretical convergence properties,...
The University of Florida was awarded a $125,701 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant will support the development of a mathematical foundation for novel artificial intelligence learning algorithms with applications to biology and engineering. Specifically, researchers will establish a theoretical framework for the minimax optimization of machine learning...
This federal Project Grant award from the National Aeronautics and Space Administration (NASA) Science Mission Directorate (CFDA 43.001 - Science) provides $182,500.00 to the Florida Institute of Technology Inc. (Florida TECH) from October 7, 2024 to October 6, 2027. The funding supports research to develop neural networks for estimating parameters of orphan afterglow from data collected by the Rubin Observatory and the Roman Space Telescope. This work aims to advance scientific understanding of...
This $365,274 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of novel mathematical techniques and algorithms for designing cost-effective space-time sampling strategies and reconstruction methods for time-evolving functions on graphs. A diverse group of researchers from Northern Illinois University will work to analyze and manage various time-evolving processes sampled under realistic conditions and...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $122,648 in funding to Iowa State University over a 3-year period from May 1, 2024 to April 30, 2027. The project aims to deliver mathematical innovations that will improve the reliability and time resolution of machine learning algorithms for national security applications, such as rapid detection and classification of potential threats. Key objectives...
This National Science Foundation (NSF) project grant, awarded under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support collaborative research to develop real-time topological data analysis capabilities for high-rate, nonlinear, and nonstationary dynamic systems. The $266,000 project, awarded on May 15, 2023 to the University of South Carolina, aims to integrate topological data analysis with machine learning to improve predictive modeling and...
This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $357,000 in funding to the University of Texas at Austin to develop new methods for understanding and forecasting the behavior of complex biological systems using data-driven approaches. The research activities funded by this 5-year award (5/1/2025 - 4/30/2030) aim to create an analytical framework that merges artificial intelligence with nonlinear dynamics theory to enable...