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SUMMARY:Graph signal processing tools for distributed sampling and topolog
 y inference
DTSTART:20160707T110000
DTSTAMP:20260407T064121Z
UID:dab6c3ef1604e2111723e35b5810bf417c3d719d490c47014a9659f3
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Alejandro Ribeiro\, University of Pennsylvania\nA networ
 k can be understood as a complex system formed by multiple nodes\, where g
 lobal network behavior arises from local interactions between connected no
 des. Often\, networks have intrinsic value and are themselves the object o
 f study. In other occasions\, the network defines an underlying notion of 
 proximity or dependence\, but the object of interest is a signal defined o
 n top of the graph. This is the matter addressed in the field of graph sig
 nal processing (GSP). Graph-supported signals appear in many engineering a
 nd science fields such as gene expression patterns defined on top of gene 
 networks and the spread of epidemics over social networks.\nTransversal to
  the particular application\, the philosophy behind GSP is to advance the 
 understanding of network data by redesigning traditional tools originally 
 conceived to study signals defined on regular domains and extend them to a
 nalyze signals on the more complex graph domain. In this talk\, we will in
 troduce the main building blocks of GSP and illustrate the utility of thes
 e concepts through real-world applications. Our focus will be on the recon
 struction of graph signals from local samples and the inference of underly
 ing graph structures from graph signal observations.\nBio: Alejandro Ribei
 ro received the B.Sc. degree in electrical engineering from the Universida
 d de la Republica Oriental del Uruguay\, Montevideo\, in 1998 and the M.Sc
 . and Ph.D. degree in electrical engineering from the Department of Electr
 ical and Computer Engineering\, the University of Minnesota\, Minneapolis 
 in 2005 and 2007. From 1998 to 2003\, he was a member of the technical sta
 ff at Bellsouth Montevideo. After his M.Sc. and Ph.D studies\, in 2008 he 
 joined the University of Pennsylvania (Penn)\, Philadelphia\, where he is 
 currently the Rosenbluth Associate Professor at the Department of Electric
 al and Systems Engineering. His research interests are in the applications
  of statistical signal processing to the study of networks and networked p
 henomena. His focus is on structured representations of networked data str
 uctures\, graph signal processing\, network optimization\, robot teams\, a
 nd networked control. Dr. Ribeiro received the 2014 O. Hugo Schuck best pa
 per award\, the 2012 S. Reid Warren\, Jr. Award presented by Penn's underg
 raduate student body for outstanding teaching\, the NSF CAREER Award in 20
 10\, and paper awards at the 2015 Asilomar Conference on Signals Systems a
 nd Computers\, the 2013 American Control Conference\, as well as the 2006 
 and 2005 International Conferences on Acoustics\, Speech and Signal Proces
 sing. Dr. Ribeiro is a Fulbright scholar and a Penn Fellow.
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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