This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award (CFDA 47.070) for $385,000 will enable the University of Maryland, College Park to develop artificial intelligence (AI) systems that can provide personalized, appropriate responses to users based on their individual background and needs. The project aims to first construct a diverse dataset to characterize preferred responses from different user groups, and then use this to train AI...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) provides $800,000 in funding from September 1, 2024 to August 31, 2027 to the University of Illinois at Urbana-Champaign. The project focuses on enhancing the safety of large language models (LLMs) used in high-stakes applications by developing quantifiable safety measures and algorithms to detect and mitigate unsafe behaviors. Key technical aims include ensuring...
The National Science Foundation Division of Behavioral and Cognitive Sciences awarded a $200,000 Project Grant under the Social, Behavioral, and Economic Sciences federal grant program (CFDA 47.075) to the University of Illinois on February 15, 2022. The grant will support research to develop new evaluation and training paradigms for inclusive automatic speech recognition over a three-year period ending January 31, 2025. Specifically, the university will create open-source black-box and...
This Project Grant award from the National Science Foundation's Division of Information and Intelligent Systems (CFDA 47.070 - Computer and Information Science and Engineering) supports research into probing the inner workings of artificial intelligence (AI) systems and comparing them to human cognition during speech recognition. The $50,000 award to the University of Southern California (USC) will fund the development of novel mathematical models and experimental methods to examine how AI...
This National Science Foundation project grant of $260,147 will fund research at the University of Washington from May 2022 to April 2025 under the Computer and Information Science and Engineering program (CFDA 47.070). The research aims to improve speech technology and develop automated oral literacy assessment tools for young speakers of African American English to enhance early education outcomes. Specifically, the university researchers will develop data augmentation and normalization...
This National Science Foundation project grant of $318,850 will fund research at the University of California, Los Angeles from May 2022 to April 2025 under the Computer and Information Science and Engineering program (CFDA 47.070). The research aims to improve speech technology and develop automated oral literacy assessments to better support learning outcomes for young African American English-speaking children. Specifically, the university researchers will develop data augmentation 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...
This $175,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at Southern Illinois University (SIU) on "UNITED LEARNING: DATA-SHAREABLE HETEROGENEOUS DISTRIBUTED LEARNING". The project aims to develop new techniques for integrating low-resource devices like personal computers and IoT devices into the training of complex deep learning models. This will be achieved through two...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Project Grant award, with a total funding of $174,770, supports the development of an adaptive, federated, continuous learning system that uses a novel federated, semi-supervised learning framework. This framework aims to retrain deep neural network models on distributed, unlabeled, heterogeneous data from edge devices, while leveraging explainable AI techniques to expedite local training. The...
The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Illinois for a 4-year collaborative research project on privacy-preserving machine learning on graph-structured data. The project aims to develop innovative, efficient algorithms for training and updating large-scale graph neural network models while preserving the privacy of sensitive graph data across applications in areas...