Graph and Network Analysis

Graph and Network Science provides a mathematical and computational framework for modeling and analyzing complex systems composed of interconnected entities. It enables the study of connectivity patterns, information flow, structural organization, and system dynamics. Integrating graph theory, optimization, statistics, machine learning, and network science, this field supports the discovery of hidden relationships, identification of key components and communities, and prediction of system behavior in large-scale and high-dimensional data. Applications span computational biology, social networks, transportation, communication systems, and artificial intelligence.