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K-State Epicenter

K-State Epicenter

Kansas State University
Electrical and Computer Engineering
3083 Engineering Hall
Manhattan, KS 66506

Phone: (785) 532-4646

Hours: 8 am-12pm, 1pm-5pm M-F

Network partitioning for mitigation of epidemics

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PIs: Caterina Scoglio

Student: Phillip Schumm.

Abstract

This project aims to explore the applicability of network partitioning to epidemic management and control. The current focus of this work is on a metric known as modularity that serves as an objective function to sort nodes into communities such that nodes are well-connected within communities and sparsely connected between communities. The assignments of nodes into communities could be useful as either possible quarantine strategies or regional threat classifications.

Presentations & Publications

P. Schumm and C. Scoglio. Bloom: A Stochastic Growth-based Fast Method of Community Detection in Networks, Journal of Computational Science, Journal of Computational Science, Volume 3, Issue 5, September 2012, Pages 356–366.