Community Detection in Real World Complex Mobility Networks

Team: Delineo Clustering

Program: Computer Science

In the past two years, we have observed the coronavirus (COVID-19) pandemic evolve into a public health crisis and challenge all over the world. To answer how the disease spreads, we need to first study how people interact. The demand for community detection in real-world mobility networks then thrived. Community detection in networks has always been an important research topic in computer science. However, in the context of mobility networks, the connections between people are unprecedentedly strong, making community detection in these networks particularly challenging. In this project, we tackle this problem by proposing innovative computer science methods and augmenting classical algorithms with modern strategies to discover the community structures in large-scale mobility networks.