This $207,737 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to develop a new class of machine learning models called "Programmatic Foundation Models" that can efficiently analyze large-scale satellite, aerial, and ground imagery. The goal is to create interpretable, robust AI models that can understand global and local phenomena from images, providing insights...
This $200,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will enable Carnegie Mellon University (CMU) to develop advanced spatiotemporal foundation models and generative AI capabilities for large-scale multimodal threat detection. The project aims to create new data representations and neural network architectures to scale up existing spatial detection algorithms, enabling the rapid deployment of analytical...
This Project Grant award for $180,000.00, provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences federal grant program (CFDA 47.049), aims to advance the mathematical understanding of trustworthy artificial intelligence (AI) algorithms for threat detection. The primary objectives are to investigate few-shot learning techniques, which can build effective models from a very limited number of data samples, and to explore few-shot graph generation methods,...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal Project Grant award, with CFDA number 47.070, provides $400,000 in funding to Temple University to develop a novel Wi-Fi-based system for detecting suspicious objects hidden in baggage. The project aims to enhance public safety by creating a low-cost, portable solution that can be deployed in a wide range of public venues beyond just high-security areas. The award supports the design and...
This federal Project Grant award, provided by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), will support research on optimization techniques and geometrically constrained neural networks for threat detection. The $250,000 award to Colorado State University (CSU) will run from September 1, 2024, to August 31, 2027. The research will focus on adapting and tuning mathematical tools, including geometry, topology, optimization, and machine learning,...
This $125,000 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports a collaborative research project on developing improved graph neural network (GNN) algorithms for threat detection. The key research objectives are to: 1) maintain accuracy with deep GNNs, 2) enable GNN training with limited data, and 3) reduce computational costs for training and deploying deep GNNs with...
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 Project Grant award from the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) provides $712,258 to the University of Central Florida (UCF) to acquire an integrated LiDAR and hyperspectral sensing system. The goal is to capture and integrate visible and invisible data using this new sensing system, which will be mounted on drones, robots, and ground vehicles. This will enable researchers to monitor and analyze structural and environmental changes over time...
The National Science Foundation (NSF) awarded a $240,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Central Florida (UCF) Board of Trustees Office of Research. The grant supports a 3-year research project to develop a theoretical analysis that sheds light on the robustness of neural network-based methods and the properties of adversarial training. The research aims to contribute to the development of more robust neural network-based...
This $600,000 Project Grant awarded by the National Science Foundation (NSF) Division of Computing and Communication Foundations will fund the development of an innovative aerial imaging system that incorporates state-of-the-art artificial intelligence (AI) for real-time data processing and analysis. The project, titled "CISE-MSI:DP:REAL-TIME AERIAL IMAGING WITH EDGE AI," is a collaboration between students and faculty at Norfolk State University (NSU), a minority-serving institution...