This $1,500,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) is for the University of Notre Dame to develop an AI-driven paradigm to promote community resilience and prevent opioid misuse and addiction among teenagers and young adults (TYAs). The key products and services to be delivered under this 4-year grant include: 1) Using graph neural networks and self-supervised/prompt learning...
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...
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...
The National Science Foundation awarded a $515,999 Project Grant to the University of Notre Dame under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to develop comprehensive methods for learning to augment graph data through machine learning algorithms. Over a three-year period from March 2022 to February 2025, the University will deliver novel techniques to augment graph data by counterfactual inference on edges as treatment variables, forecasting...
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 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...
The National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems awarded a $399,541 Project Grant to the Trustees of Dartmouth College to develop a high-throughput, label-free, and portable sensor that can quantitatively detect multiple illicit drugs including opioids, cocaine, psychostimulants, and methadone in liquid samples such as biofluids. The project aims to create a silver or gold nanoparticle-decorated zinc oxide nanorod coated silica nanofiber matrix...
This federal Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program provides $649,585 to Auburn University to develop an integrated and miniaturized opioid sensor system. The project aims to address the opioid crisis through innovative, cost-efficient, and portable opioid biosensors that can enable real-time, accurate detection and monitoring. The interdisciplinary team is working to deliver solutions for law...
The National Science Foundation awarded a $150,000 Project Grant to the University of Notre Dame du Lac to develop a holistic framework for detecting online opioid trafficking activities. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), this two-year award will support the design of a heterogeneous temporal graph and graph transformer model with meta-learning capabilities. The framework aims to comprehensively model and analyze dynamic multi-modal data from social media to help combat the opioid epidemic. Specifically, the university will propose a novel heterogeneous temporal graph to represent relational information from social media posts over time. Researchers will then develop a graph transformer to learn user representations and identify opioid traffickers. Finally, they will create a new meta-learning algorithm to enable the model to quickly adapt to new tasks using limited labeled data, such as identifying emerging opioid types and associated traffickers. Outcomes from this project intend to benefit data mining, machine learning, and public health domains.