Sayan Banerjee receives CAREER grantDecember 28, 2021
Sayan Banerjee received an NSF CAREER grant on
Network Centrality and Its Applications in Detection, Dynamics, and Load Balancing
The project aims to develop a universal mathematical understanding of networks that evolve over time and processes that live on them. The key idea is to identify certain network attributes that carry a footprint of a network's past as it evolves and exploit them in reconstructing the early stages of a network from its current configuration. This can be used to detect the origin of a rumor spread, popular individuals and their influence in a social network, or a source of a disease outbreak. Another key research direction is the systematic understanding of how local interactions in a large network influence its global geometry. This can be used to increase the net efficiency of a network of servers through cooperative local interactions that will have a long-term impact in improving routing schemes at airport security, big supermarkets, and distribution of vaccines and antidotes.