Project Grant 2228243
- This $600,000 Project Grant was awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The project aims to advance the fundamental research on detecting AI-generated fake images by focusing on understanding the generalization capabilities of fake image detectors. Specifically, the project will investigate two main thrusts: (1) understanding the characteristics that make AI-generated images fake, including the role of...
- This $274,936 Project Grant awarded by the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development and validation of innovative technology capable of learning to infer from unlabeled time series financial data. The project aims to address technical hurdles in machine reasoning of qualitative financial information, reliance on human annotation, difficulties with transfer learning, and scarcity of labeled financial...
- This National Science Foundation (NSF) award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $554,699 to Georgia Tech Research Corporation (Georgia Tech) to develop a distributed FPGA (field-programmable gate array) system for real-time fraud detection on large-scale dynamic financial activity graphs. The project aims to achieve microsecond-level latency in detecting fraudulent transactions using graph neural networks (GNNs), which is a significant...
- The National Science Foundation (NSF) awarded a $1,498,856 Project Grant under its Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) to the University of Illinois to develop an integrated, open-source ecosystem called OpenAD for anomaly detection. The project aims to unify existing open-source anomaly detection systems into a comprehensive platform that supports diverse data types and application domains. Key goals include establishing a standardized development environment,...
- Federal Project Grant Award Summary University of California, Merced received a $175,000 project grant from the National Science Foundation's Division of Information and Intelligent Systems (CISE program, CFDA 47.070) awarded June 15, 2025, with completion targeted for May 31, 2027. This Computer and Information Science and Engineering (CISE) grant supports the development of trustworthy artificial intelligence (AI) systems that synergistically integrate large language models with knowledge...
- This $200,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) aims to develop novel feature selection techniques for supervised and unsupervised machine learning models. The research will focus on the "knockoff method" for identifying key predictive features while controlling false discoveries, incorporating microbiome data structures, handling missing values, and...
- The National Science Foundation (NSF) awarded a $1,182,881 Project Grant to the University of California, San Diego (UCSD) under the NSF's Computer and Information Science and Engineering program (CFDA 47.070). The grant supports the development of new methods to ensure that machine learning models assigned to decisions such as lending and hiring can be changed through individual actions, protecting the right to access these services. The project will create techniques for (1) detecting...
- 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 $599,411 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 "Trustworthy Toolbox for Double-Correct Predictive Modeling in Sciences." The project aims to create advanced artificial intelligence (AI) and machine learning (ML) models that can make accurate predictions while also providing transparent, scientifically-grounded rationales for their outputs. This...
- The National Science Foundation awarded the University of Missouri at Kansas City a two-year, $105,600 Project Grant under the STEM Education federal grant program (CFDA 47.076) to develop and evaluate the use of visualized and explainable artificial intelligence to improve digital forensics education. The University will explore how AI technologies can personalize learning experiences and provide real-time feedback to students studying digital forensics. As the prime awardee, UMKC will leverage...
The National Science Foundation awarded a $100,000 Project Grant to the University of California, Merced under the NSF Technology, Innovation, and Partnerships federal grant program (CFDA 47.084) to develop artificial intelligence models for financial fraud detection. Specifically, the university will use tree-based machine learning techniques to create fraud detection software with predictive accuracy exceeding industry standards. The software aims to save banks millions annually by reducing false positives and processing transactions faster through more explainable and trustworthy models. The university's new optimization-based algorithm seeks superior fraud detection solutions at scale for commercial applications in banking and other sectors such as credit, legal, government, and public health.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $50.0k | 6/13/22 |