Project Grant 2214376
- This federal Project Grant award of $320,000, awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, is for a collaborative research project to design and develop a data-driven, AI-augmented paradigm to investigate the intersection of poverty-driven food insecurity and the opioid crisis. The goal is to develop integrated, personalized interventions to address this intertwined societal challenge and enhance public health,...
- This $180,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is for a collaborative research project to develop a data-driven, AI-powered system to investigate the nexus of poverty-driven food insecurity and the opioid crisis. The goal is to design integrated, personalized interventions to address these intertwined societal challenges and enhance national public health, safety, and welfare. The award,...
- This Project Grant award in the amount of $311,024 was provided by the National Science Foundation (NSF) under the Engineering (CFDA 47.041) program. The grant supports a collaborative research project led by West Virginia University Research Corporation to develop novel analytical methods and decision support models to help county policymakers in West Virginia effectively allocate resources to combat the opioid crisis. The project aims to map and compare county-level budgetary approaches to...
- This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $670,000 to The Pennsylvania State University (Penn State) to develop a data-driven early warning system framework for detecting and responding to emerging epidemics of illicit substance use. The project aims to (1) create predictive models to identify high-risk communities and emerging threats, (2) uncover causal factors driving these substance use patterns, (3) optimize intervention...
- This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $244,008 to The Research Foundation for the State University of New York (SUNY) to develop novel analytical methods and decision support models to help county policymakers in West Virginia more effectively combat the opioid crisis. The project aims to assess the effectiveness of interventions that disrupt opioid supply chains, including both supply-side interdiction strategies and...
- This $599,573 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports the University of Notre Dame's research to develop a new machine learning paradigm for effective yet efficient foundation graph learning models (FGLMs). The project aims to create techniques, methods, and models for FGLMs that can be widely applied in areas like scientific research, social network analysis, anomaly detection, drug...
- This $478,962 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) to Clemson University aims to mitigate the harm caused by illicit opioid use, particularly fentanyl, through a convergent research approach. The project will investigate methods to disrupt the supply chain of illicit opioids and shift user pathways towards recovery, while optimizing the allocation of resources between demand- and supply-side interventions. Key research...
- This Project Grant award from the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) supports a collaborative research project titled "Disrupting West Virginia's Opioid Crisis: A Multi-Disciplinary Approach through Interdiction and Harm Reduction". The $238,666 award to the Regents of the University of Minnesota aims to develop novel analytical methods and decision support models to help county policymakers in West Virginia effectively allocate resources to...
- This $220,000 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program supports the development of advanced computational methodologies for drug discovery and development. The primary awardee, the Regents of the University of Minnesota, will create a comprehensive generative AI framework capable of efficiently generating high-quality drug candidates with multiple desired properties. This initiative aims to expedite...
- This $250,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports the development of algorithms for real-time dynamic risk identification and monitoring of streaming data, particularly in the domains of electronic medical records, mobile health, and supply chain. The key objectives are to create a unified framework for dynamic risk detection that can be incorporated into...
This National Science Foundation Project Grant of $390,004 supported research at the University of Notre Dame du Lac from November 1, 2021 to September 30, 2022 under the Computer and Information Science and Engineering program (CFDA 47.070). The award funded the development of a novel computational framework to construct a heterogeneous network from multiple data sources and extract useful information to reduce risks of opioid overdoses resulting from polypharmacy. Key deliverables included constructing a heterogeneous network representation from multiple data sources; developing scalable techniques for large-scale and dynamic heterogeneous network representation learning; and designing a new deep learning framework with interpretability enhancements for early detection of risky drug-drug interaction patterns involving opioids combined with other medications. Outcomes aimed to benefit public health through overdose prevention and advance intelligent information management involving multiple data sources.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $390.0k | 2/11/22 |