Project Grant 80NSSC20K1193

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 $125,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will enable the Florida Institute of Technology Inc. (Florida TECH) to utilize advanced machine learning algorithms to efficiently analyze and predict information within high-dimensional data matrices and tensor computations related to state-space dynamical systems. The key objectives are to: (I) utilize machine learning to predict future states of dynamical...

The Department of the Air Force Materiel Command Research Laboratory awarded a $300,000 Project Grant under the Air Force Defense Research Sciences Program (CFDA 12.800) to the University of Cincinnati Sponsored Research Services Division. The grant supports the development of physics-enhanced deep learning models for fast-than-real-time prediction of dynamic behavior in space robotic systems. The three-year project will leverage the university's expertise in aerospace engineering and machine...

This $348,127 National Science Foundation (NSF) award under the Geosciences program (CFDA 47.050) supports collaborative research to develop new physics-informed machine learning and stochastic modeling techniques for improving magnetohydrodynamics (MHD) simulations of the interaction between the solar wind and Earth's magnetosphere. The University of California, Los Angeles (UCLA) will lead this 3-year project, which aims to enhance the performance of global magnetosphere MHD models used for...

This three-year, $1,194,210 project grant from the National Science Foundation's Geosciences program (CFDA 47.050) will support the development of empirical and physics-informed machine learning models of collisionless shock waves. The Johns Hopkins University will utilize over 10,000 crossings of Earth's bow shock from NASA spacecraft to create a parameterized, three-dimensional model of the global bow shock structure. Additionally, the researchers will develop a model for general collisionless...

The University of California, Santa Cruz (UCSC) has been awarded a $2,499,579 Project Grant from the Air Force Defense Research Sciences Program (CFDA 12.800) to develop "DIGITAL TWIN ENABLED AUTONOMOUS CONTROL FOR ON-ORBIT SPACECRAFT SERVICING." This 3-year grant, awarded on September 25, 2023, aims to increase the resilience and availability of space assets through research on autonomous on-orbit servicing, refueling, repair, and towing/decommissioning. UCSC is collaborating with...

The National Science Foundation (NSF) Directorate for Engineering awarded a 5-year, $626,006 CAREER grant to The Pennsylvania State University, doing business as Penn State, to support research that enables dynamic modeling, control, and design for next-generation autonomous aerial systems with enhanced capabilities and operational efficiency. The project aims to establish a foundational framework that could revolutionize the entire lifecycle of autonomous systems, from production to...

This $500,000 project grant, awarded on January 1, 2024 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to address the urgent need for end-to-end safety in learning-enabled autonomous systems across various application scenarios, such as self-driving cars and urban air mobility. The project, titled "COLLABORATIVE RESEARCH: SLES: GUARANTEED TUBES FOR SAFE LEARNING ACROSS AUTONOMY ARCHITECTURES,"...

This EAGER (Early-Concept Grants for Exploratory Research) award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will develop generative artificial intelligence (AI) methods to learn from computational physics simulations and mathematical equations. The $300,000 project aims to expand the capabilities of large language models, such as OpenAI's ChatGPT and Microsoft's Copilot, to go beyond text-based learning and make predictions on complex, coupled physics problems...

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...