Network Science and Engineering Group

Spreading Processes over Multilayer and Interconnected Networks

Multilayer

This project advances the boundaries of network theory by analyzing spreading processes over multilayer and interconnected networks, which abound in nature and man-made infrastructures, and about which many interesting questions remain unanswered. Multilayer networks are an abstract representation where multiple types of links exist among nodes. Interconnected networks are an abstract representation where two or more simple networks, possibly with different and separate dynamics, are coupled to each other. The rationale for this project is that viral-spreading dynamics over multilayer and interconnected networks exhibit behaviors that cannot be attributed to single-network characteristics and play a highly relevant role in practice. This project uses rigorous mathematical tools from network science, spectral graph theory, nonlinear dynamics, stochastic processes, controls, game theory, and optimization.

Duration July 2014 - June 2018

Investigators

Faculty

Caterina Scoglio (Google Profile)

Faryad Darabi Sahneh (Google Profile)

Piet Van Mieghem (Google Profile)

Jose Marzo (Google Profile)

Students

Aram Vajdi

Josh Melander (former)

Futing Fan (former)

Products

Journals

F. D. Sahneh, C. Scoglio, P. Van Mieghem (2015)
Exact Coupling Threshold for Structural Transition Reveals Diversified Behaviors in Interconnected Networks.
Physical Review E 92 (4)

Scoglio CM, Bosca C, Riad MH, Sahneh FD, Britch SC, Cohnstaedt LW, et al. (2016)
Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies.
PLoS ONE 11(9)

Riad MH, Scoglio CM, McVey DS, Cohnstaedt LW (2016)
An individual-level network model for a hypothetical outbreak of Japanese encephalitis in the USA
Stoch Environ Res Risk Assess

Shakeri H, Albin N, Sahneh FD, Poggi-Corradini P, Scoglio CM (2016)
Maximizing algebraic connectivity in interconnected networks
Phys. Rev. E 93

F. D. Sahneh, V. Preciado, and C. Scoglio (2016)
Epidemic Spreading in State-Dependent LocallyAdaptive Networks.
Submitted

D Juher, J Saldaña, R Kohn, K Bernstein, C Scoglio (2017)
Network-Centric Interventions to Contain the Syphilis Epidemic in San Francisco
Scientific Reports 7

F.D. Sahneh, A. Vajdi, H. Shakeri, F. Fan, C. Scoglio (2017)
GEMFsim: a stochastic simulator for the generalized epidemic modeling framework
Journal of Computational Science

Conferences

J. Marzo, S. Gomez-Cosgaya, C. Scoglio
Network Robustness Simulator: a Case Study on Epidemic Models
In Proceedings of the 9th International Workshop on Resilient Network Design and Modeling, Alghero (2017)

M. Riad, C. Scoglio, D. S. McVey and L. W. Cohnstaedt
Estimation of Parameters and Basic Reproductive Ratio for Japanese Encephalitis Transmission in the Philippines using a Sequential Monte Carlo Filter
In Proceedings of the 1st IEEE Conference on Control Technology and Applications, Hawaii (2017)

F. D. Sahneh, A. Vajdi, C. Scoglio
Delocalized Epidemics: A Maximum Entropy Approach.
In Proceedings of the American Control Conference, Boston (2016)

P. Van Mieghem, F. D. Sahneh, C. Scoglio
An Upper Bound for the Epidemic Threshold in Exact Markovian SIR and SIS Epidemics on Networks.
In Proceedings of the IEEE 53rd Annual Conference on Decision and Control (CDC), Los Angeles (2014)

Outreach

________________________________________________________________________________________________

Supported by National Science Foundation under Award CIF-1423411. Any opinions, findings, and conclusions or recommendations expressed in this website are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.