Spreading Processes over Networks: Theory and Applications

Event Date: January 14, 2020
Time: 10:30 am
Location: MSEE 239
Priority: No
School or Program: Electrical and Computer Engineering
College Calendar: Show

Philip E. Paré
KTH Royal Institute of Technology

Abstract
The study of spreading 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 spreading processes focused on spread 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 and misinformation over social networks.  Up to this point these network-dependent spread models have not been validated by real data.

In this talk, I present and analyze mathematical models for network-dependent spread. I use the analysis to validate the first model employing John Snow's classical work on cholera epidemics in London in the 1850's. Given the demonstrated validity of the model, I discuss several control strategies for mitigating spread, and formulate a tractable antidote administration problem that significantly reduces spread. Motivated by competing USDA farm subsidy programs, I present and analyze a model for multiple competing viruses spreading over multi-layered networks. Further, I present a technique for estimating the healing and infection parameters of the model from time series data. I validate the multi-virus model by applying this technique to the USDA farm subsidy dataset, and improve upon the results by employing an online learning algorithm. Finally, motivated by recent contaminated water-related outbreaks in Scandinavia, I propose a layered infrastructure network model and explore when the source of an outbreak can be detected. I conclude my talk by discussing various directions for compelling future work, including combining the online learning algorithms with the control techniques to develop data-driven mitigation strategies.
 
Bio
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, and his Ph.D. in Electrical and Computer Engineering (ECE) from the University of Illinois at Urbana-Champaign (UIUC), Urbana, IL in 2018. He is currently a postdoctoral scholar in the Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science at KTH Royal Institute of Technology in Stockholm, Sweden. Philip was the recipient of the 2017-2018 Robert T. Chien Memorial Award for excellence in research from the UIUC ECE Department and named a 2017-2018 UIUC College of Engineering Mavis Future Faculty Fellow. His research interests include the modeling, control, and security of dynamic networked systems, such as, epidemiological, infrastructure, biological, economic systems, and social networks.
 
Host
Professor Christopher Brinton, cgb@purdue.edu
 

2020-01-14 10:30:00 2020-01-14 11:30:00 America/New_York Spreading Processes over Networks: Theory and Applications MSEE 239