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UID:20260619T001843EDT-2249POJdkP@132.216.98.100
DTSTAMP:20260619T041843Z
DESCRIPTION:Virtual Informal Systems Seminar (VISS) Centre for Intelligent 
 Machines (CIM) and Groupe d'Etudes et de Recherche en Analyse des Decision
 s (GERAD)\n\n\n	Zoom Link\n\n	Meeting ID: 910 7928 6959        \n		Passcode: V
 ISS\n\n\n \n\nSpeaker: Philip Paré\, Purdue University\n	\n	Abstract: In thi
 s talk\, we explore how networked compartmental models of epidemic process
 es combined with transportation data can be used to model the spread of CO
 VID-19. We first employ a networked SEIR (susceptible-exposed-infected-rec
 overed) model and present necessary and sufficient conditions for identify
 ing the model parameters from data. We illustrate several shortcomings of 
 traditional approaches by applying the identification results to COVID-19 
 testing and travel data from the Northeastern United States and use these 
 inaccuracies as motivation for the latter two parts of the talk. One typic
 al error is assuming that testing data perfectly capture the underlying ep
 idemic states\, which is not accurate due to delays in testing results\, t
 esting inaccuracies\, and biased/partial population sampling. We present a
 n algorithm for inferring the underlying epidemic states of an SIR model f
 rom testing data that accounts for heterogeneous delays and a closed-form 
 expression for the error of the algorithm. The last part of the talk focus
 es on the recent development of a networked SEIR model that incorporates p
 opulation flow as the viral spread mechanism to capture infection transmis
 sion between sub-populations. We show\, under reasonable assumptions\, tha
 t the dynamics have a consensus-type behavior where in steady-state each s
 ub-population has the same amount of recovered individuals. Employing this
  model\, we present several approaches for using travel restrictions as a 
 control mechanism.\n\n \n\nBio: Philip E. Paré is an Assistant Professor i
 n the School of Electrical and Computer Engineering at Purdue University. 
 He received his Ph.D. in Electrical and Computer Engineering from the Univ
 ersity of Illinois at Urbana-Champaign in 2018\, after which he went to KT
 H Royal Institute of Technology in Stockholm\, Sweden to be a Post-Doctora
 l Scholar from 2019-2020. He received his B.S. in Mathematics with Univers
 ity Honors and his M.S. in Computer Science from Brigham Young University 
 in 2012 and 2014\, respectively. At the University of Illinois\, he was th
 e recipient of the Robert T. Chien Memorial Award for excellence in resear
 ch and named a Mavis Future Faculty Fellow.  His research focuses on netwo
 rked control systems\, namely modeling\, analysis\, and control of virus s
 pread over networks.\n
DTSTART:20210416T180000Z
DTEND:20210416T190000Z
LOCATION:CA\, ZOOM
SUMMARY:Epidemic Spread with Transportation: Modeling\, Inference\, and Con
 trol
URL:/cim/channels/event/epidemic-spread-transportation
 -modeling-inference-and-control-330317
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