The National Science Foundation (NSF) awarded a $175,000 Project Grant under the Mathematical and Physical Sciences (MPS) program to North Carolina State University (NC State) for the project "Scalable and Generalizable Inference for Network Data". The project aims to advance the statistical analysis of complex digital networks by addressing challenges in accurately reflecting network realities and efficiently managing their vast scales. Key products and services to be delivered include:
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Developing novel statistical methods and computational tools to enable more reliable anomaly detection and robust analysis of large-scale networks. This includes introducing two new algorithms, Predictive Subsampling (PREDSUB) and Aggregative Subsampling with Common Overlap (ASCO), to augment existing statistical methods for application to large datasets.
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Conducting thorough theoretical analysis and empirical validation of the new methodologies, leveraging collaborations across disciplines such as epidemiology and digital health.
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Implementing educational and interdisciplinary initiatives to equip the next generation of scientists, ensuring sustained impact across disciplines and contributing to the public good through engagement and nonprofit collaborations.
The award period is from July 1, 2024 to June 30, 2027.
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