The National Science Foundation (NSF) awarded a $300,000 Project Grant under CFDA 47.070, the Computer and Information Science and Engineering (CISE) federal grant program, to The Pennsylvania State University (Penn State) to develop a real-time crowd-sourced geospatial digital twin (GDT) for cyber-physical systems. The project aims to enhance the delivery of vital information to smart mobile devices by leveraging crowd-sourced data and human-in-the-loop strategies. Key research areas include...
This National Science Foundation (NSF) Engineering Program (CFDA 47.041) project grant award of $600,000 to The Ohio State University aims to establish an intellectual foundation for building a real-time, crowd-sourced geospatial digital twin (GDT). The project will develop novel approaches for ensuring timely, truthful, and unbiased data collection from the community to update GDTs, which provide digital models of physical environments for applications like monitoring, maintenance, and...
This $2,228,505 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 cloud-based, open, and collaborative cyberinfrastructure to enable data-driven exploration and modeling of urban data. The project aims to address two critical obstacles in urban computing: the lack of robust, well-engineered tools and open computing platforms, and the dispersed community of cross-disciplinary...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) aims to revolutionize the understanding and prediction of human mobility patterns. The $300,000 award to Lehigh University, to be executed from September 1, 2024 to August 31, 2027, will support the development of privacy-preserving, federated neural networks to analyze large-scale, cross-domain human mobility data from sources like smartphones, payment...
This federal Project Grant award of $180,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop new methods for privacy-preserving data sharing and collaborative analysis of mobile internet measurement data. The key products and services to be delivered under this 2-year award, which begins on October 1, 2024, include: 1) Quality-explainable data synthesis and augmentation techniques, 2) Privacy-preserving...
This Project Grant award, funded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports the development of a cyberinfrastructure to catalyze and sustain the urban computing community. The $1,021,495 award, effective September 1, 2024 through August 31, 2029, aims to create open-source, scalable, and interoperable tools and methods for exploring urban data. The cyberinfrastructure will enable a collaborative environment for...
This $299,574 federal Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop a comprehensive cyberinfrastructure solution for training large-scale Graph Neural Networks (GNNs) to support spatiotemporal prediction and modeling of geographically distributed and heterogeneous data. The project led by Emory University will address key research challenges in formulating spatiotemporal prediction within a...
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 Utah Office of Sponsored Projects Division. The grant, awarded on June 15, 2023, will fund a project to build a foundational model for human mobility that can incorporate diverse types of movement, temporal, and socio-demographic data. The model will utilize machine learning techniques to generate outputs relevant to both...
This $330,000 Project Grant award was provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049). The project will develop new AI-based techniques to detect anomalous behavior of individuals and groups based on their GPS location data. The investigators will create a temporal graph neural network (GNN) to characterize normal and abnormal location behavior patterns, and a dynamic graph anomaly detection (DGAD) approach to...
This $250,000 Project Grant awarded by the National Science Foundation (NSF) under its Computer and Information Science and Engineering (CFDA 47.070) program will support research to improve public decision-making through the development of statistical methods to understand biases in crowdsourced data. The project, titled "CAREER: Public Decision-Making with Crowdsourced Data", aims to: Measure biases in public crowdsourcing of incident reports and community health monitoring data,...