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...
This $439,425 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research to enable the safe deployment of learning-enabled systems that can robustly learn and optimize their behavior based on uncertain human feedback and intent. The key objectives are to: (1) develop methods for providing probabilistic performance guarantees when learning policies from human input,...
This $271,343 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports a collaborative research project to explore new methods for designing learning and inference systems that are robust to distributional uncertainty and data corruption. The project aims to advance research in areas such as statistical learning, optimization, control theory, network science,...
This National Science Foundation (NSF) Project Grant award to Purdue University, under the Computer and Information Science and Engineering program (CFDA 47.070), focuses on developing novel technologies to enable robust, fair, and explainable data-driven decision-making systems. The $466,411 award, effective July 1, 2023 through June 30, 2028, will fund research to: 1) detect and mitigate biases in machine learning model outcomes, 2) assess the validity of data for learning fair and trustworthy...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of South Carolina. The grant, with a period of performance from October 1, 2024 to September 30, 2027, focuses on enhancing security and mitigating harm in AI-generated vision language models. Key technical objectives include: 1) Developing a prompting framework for detecting harmful content provenance in AI-generated vision...
This federal Project Grant award for $209,421 was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award aims to develop a framework that integrates real-time safety verification and assurance into the performance optimization process of AI-driven safety-critical systems, such as self-driving cars and surgical robots. The project will devise innovative real-time scheduling strategies and safe...
This $149,951 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports a collaborative research effort between Oakland University and Worcester Polytechnic Institute. The project aims to increase awareness and promote broader adoption of the National AI Research Resource (NAIRR) pilot by organizing two 12-workshop series over two years. These workshops will provide hands-on training for...
This $281,635 federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support research at the University of Rochester on declarative AI data cleaning with performance guarantees. The project aims to develop a novel paradigm for model-driven data cleaning that jointly optimizes data quality and downstream machine learning model performance across various data modalities. Key focus areas include...
This $299,977 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project between U.S. and Australian researchers to develop AI-powered approaches for addressing societal challenges in areas such as drought resilience, emissions reduction, and infectious disease response. The key objectives are to establish theoretical and algorithmic foundations for responsible and...
This $414,995 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop personalized artificial intelligence (AI) systems that can tailor their responses to individual users based on their unique backgrounds and needs. Key objectives include: Gathering a diverse dataset to characterize the types of responses preferred by different people, particularly underrepresented groups. Using this data to...