This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $400,000.00 to the University of California, Berkeley (UC Berkeley) to conduct research on understanding, visualizing, and attributing multimodal generative models - large-scale AI models that generate both text and images. The research aims to develop new systematic frameworks for analyzing the internal mechanisms 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...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $596,797 to the University of California, San Diego (UCSD) from September 1, 2024 to August 31, 2027. The project aims to develop automated frameworks for interpreting neural networks and designing robust, human-understandable neural network models. Key objectives include: (1) automating interpretations that describe the internal functioning of deep...
This Project Grant award of $500,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research to understand and mitigate security vulnerabilities in machine learning (ML) models. The research aims to characterize how malicious actors could exploit the unused parameters in trained ML models to install covert functionality, and develop mitigation approaches to improve the robustness and trustworthiness of ML...
This Project Grant award of $175,000.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research at the University of California, Davis (UC Davis) to develop new statistical and computational methods for analyzing high-dimensional, noisy, and dynamically changing datasets. The key focus areas of the project include: (1) analyzing the robustness of manifold and deep learning algorithms for complex data; (2) developing statistical...
The University of California, San Diego (UCSD) was awarded a 5-year, $165,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The goal of this project is to develop algorithms, software, and systems that can automatically generate high-quality labeled data to mitigate the lack of labeled training data in specialized domains such as healthcare, legislation, and environmental sciences. The proposed approaches...
This $400,000 project grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models. The key objectives are to: 1) create new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2) explore model...
This $316,672 Project Grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research at San Diego State University Foundation to develop a comprehensive understanding of the robustness and computational efficiency of deep neural networks. The key focus areas include: 1) formulating theoretical frameworks for subnetwork adversarial robustness, 2) characterizing transferability through curriculum learning, and 3)...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will provide $398,990.00 to the University of California, Irvine over 3 years starting on August 1, 2025. The project aims to develop a robust theoretical framework for analyzing learning processes in multi-agent systems, such as those found in autonomous driving, economics, and artificial intelligence applications. Key goals include designing...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $391,848 to Purdue University to develop holistic systems for securing the machine learning supply chain. The project aims to create tools to quantify trust in machine learning supply chains and verify security requirements across those supply chains. The research will also support the development of a diverse next generation of computer...