Project Grant 2427915

This $300,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports a research project led by Lehigh University. The project aims to revolutionize the understanding and prediction of human mobility by leveraging large-scale data from advanced urban infrastructures and commercial systems. The key objectives are to: 1) develop domain-invariant spatiotemporal modeling techniques for human mobility prediction, 2) create new frameworks for collaborative learning across domains without compromising data privacy, and 3) design algorithms for threat detection and mobility prediction during crises. This 3-year project will utilize real-world data from two cities and incorporate 13 types of mobility data. The research is expected to result in a spatiotemporal nonlocal neural operator model, a unified framework for federated unsupervised graph learning, and domain-aware anomaly detection models for threat scenarios. The methods and tools developed will be made available as open-source software, and the project will include educational and outreach activities to promote diversity and inclusion.