Computing That Serves

Virus Spread Over Networks


Thursday, March 8, 2018 - 11:00am


Philip Paré


Sean Warnick


Colloquium presented by Philip Paré
Thursday, March 8, 2018 at 11:00 A.M.
Location: 1170 TMCB

The study of epidemic processes has been a topic of interest for many years over a wide range of areas, including computer science, mathematical systems, biology, physics, social sciences, and economics. More recently, there has been a resurgence of interest in the study of epidemic processes focused on the spread of viruses over networks, motivated not only by security threats posed by computer viruses, but also recent devastating outbreaks of infectious diseases and the rapid spread of opinions over social networks. Up to this point these network-dependent spread models have not been validated by real data. In this talk, we analyze a mathematical model for network-dependent spread and use that analysis to identify the healing and infection parameters of the model. We apply these ideas, employing John Snow’s seminal work on cholera epidemics in London in the 1850’s, to validate the susceptible-infected-susceptible (SIS) model. The validation results are surprisingly good, capturing the behavior of the cholera epidemic from John Snow’s 1854 dataset quite well. We conclude by briefly highlighting extensive analysis and algorithm design results we have obtained for time-varying and multi-layered networks, and finally discuss various directions for compelling future work.


Philip E. Paré received his B.S. in mathematics with University Honors and his M.S. in Computer Science from Brigham Young University, Provo, UT, in 2012 and 2014, respectively. He is currently an ECE Ph.D. candidate at the University of Illinois at Urbana-Champaign, Urbana, IL completing his research thesis of the study of analysis and algorithm design for virus spread over networks. He is a 2017-2018 College of Engineering Mavis Future Faculty Fellow and recently appeared on the University of Illinois List of Teachers Ranked as Excellent by Students, with Outstanding Ratings, for Fall 2017. Philip grew up in Cambridge, MA. His research interests include the modeling and control of dynamic networked systems, dimensionality reduction techniques, and time-varying systems.