Project Grant 2335967
- This $659,809 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the development of a novel system to identify cognitive and affective states, behavioral patterns, and contextual factors contributing to medical errors. The research team at Virginia Polytechnic Institute & State University (Virginia Tech) will implement multi-modal machine-learning algorithms leveraging data from...
- 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 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $519,645 to the University of Toledo Health Science Campus Division will develop a novel system to identify cognitive and affective states, behavioral patterns, and contextual factors contributing to medical errors. The project, titled "Collaborative Research: SCH: Clinical Adaptive Performance Enhancement through Human-AI Teaming (CAPE-HAT)," aims...
- This $400,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research at The Ohio State University to develop theoretical and algorithmic foundations for building a safe and reliable human-AI ecosystem. The key objectives are to: 1) create an analytical framework to characterize human-AI interactions and safety components, 2) examine feedback effects between agents and the...
- This Project Grant award from the National Science Foundation (NSF) under CFDA 47.070 - Computer and Information Science and Engineering is for $395,927 over the period of Sep 1, 2024 to Aug 31, 2027. The award aims to develop theoretical and algorithmic foundations for building a safe and robust human-AI ecosystem, where machine learning (ML) and artificial intelligence (AI) techniques are used in applications involving humans, such as recommendation systems, lending, and healthcare. The key...
- Federal Grant Award Summary The University of Virginia received a $200,000 Early-Concept Grant for Exploratory Research (EAGER) award from the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), effective October 1, 2025 through September 30, 2027. This project develops concept-based reasoning approaches to enhance the interpretability and accountability of deep neural networks...
- The University of Central Florida Board of Trustees received a $150,000 Project Grant award from the National Science Foundation Office of Emerging Frontiers and Multidisciplinary Activities to augment healthcare professionals' training, expertise development, and diagnostic reasoning with AI-based immersive technologies in telehealth. The grant was awarded on January 1, 2022 under the Social, Behavioral, and Economic Sciences federal grant program (CFDA 47.075) to contribute to basic research...
- This $666,667 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop innovative mathematical algorithms to enable safe automated patient monitoring, treatment guidance, and reconciliation of potentially conflicting medical treatments. The research will advance control theory, inference, and optimization to create new knowledge, leading to transformative approaches for coordinating complex interacting...
- This $170,000 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop robust and human-aligned deep learning techniques for analyzing medical sensor time-series data. The primary goals are to: 1) identify input confounders that lead to spurious correlations in time-series data, 2) design knowledge-editing strategies to correct these spurious correlations, and 3) investigate the techniques...
- Federal Project Grant Award Summary Clemson University received a $300,000 Project Grant from the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), awarded October 1, 2025, with completion targeted for September 30, 2028. This collaborative research initiative develops technologies to enhance accessibility and safety in human-virtual personal assistant (VPA) interactions...
The National Science Foundation (NSF) awarded a $200,000 Project Grant through the Computer and Information Science and Engineering program (CFDA 47.070) to the University of South Carolina. This two-year grant supports research to develop safety-constrained virtual health assistants (VHAs) that leverage knowledge graphs to integrate clinical protocols and practice guidelines. The goal is to enable VHAs to provide accurate, safe, and transparent healthcare support while fostering improved collaboration between humans and AI. The research will produce two key outcomes: (1) applying medical guidelines to uphold safety standards in clinical settings, and (2) generating end-user friendly explanations to support verification and decision-making. This project aims to advance neurosymbolic AI techniques to facilitate robust, verifiable human-AI collaboration with applications beyond healthcare, such as autonomous vehicles and manufacturing.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 8/3/23 |