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Collaborative Research: AF: Small: Graph Analysis: Integrating Metric and Topological Pers — NSF Award to Rutgers University New B

Graphs are one of the most common types of data across various application fields in science and engineering. Graph analysis has been central for multiple communities, including the classical graph theory community, network analysis, graph optimization, as well as the modern day graph learning communities. Traditionall

Award titleCollaborative Research: AF: Small: Graph Analysis: Integrating Metric and Topological Pers
Award ID2523653
AwardeeRutgers University New Brunswick
CityNEW BRUNSWICK
StateNJ
Amount obligated$222,191
Principal investigatorFacundo Memoli
ProgramAlgorithmic Foundations
Start date01/01/2025
AbstractGraphs are one of the most common types of data across various application fields in science and engineering. Graph analysis has been central for multiple communities, including the classical graph theory community, network analysis, graph optimization, as well as the modern day graph learning communities. Traditionally, graphs are regarded as purely combinatorial objects. However, as applications of graphs proliferate, they tend to be regarded as much richer structures. For example, a graph mig
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