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Home | Seminars and Symposia | Past seminars/symposia: Thursday, October 22, 2015

DTC Seminar Series

Uncovering Latent Network Dynamics via Blind Identification of Graph Filters

by

Gonzalo Mateos
University of Rochester
Rochester, NY

Thursday, October 22, 2015
4:15 p.m. seminar
5:15 p.m. reception

405 Walter Library

Gonzalo Mateos

Over the past decade there has been a growing fascination with the complex connectedness of modern society. As modern interconnected systems grow in size and importance, while they become more complex and heterogeneous, there is an urgent need to advance a holistic theory of networks. In this talk, I will focus on modeling, identification, and controllability of distributed network processes, which are often conceptualized as signals defined on the vertices of a graph. To untangle the latent structure of such signals, the key novel insight is to view them as outputs of unobserved graph filters that model the emergence of complex network dynamics. Albeit simple, graph filters are appealing since they represent linear transformations between graph signals that can be implemented via local interactions among network nodes, and they are well-suited to model e.g., diffusion or percolation processes in the network. In this direction, I will describe novel theory and algorithms for the challenging problem of joint identification of a graph filter and its sparse input, given only an observed (output) graph signal, e.g., an opinion profile in a social network where the goal is to identify those influential actors that instilled the observed status-quo. At a fundamental level, this effort broadens the scope of classical blind system identification to networks, or, of blind deconvolution of temporal and spatial signals to less structured graph domains.

 

Gonzalo Mateos was born in Montevideo, Uruguay, in 1982. He received his B.Sc. degree in Electrical Engineering from Universidad de la Republica, Uruguay, in 2005, and the M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Minnesota, Twin Cities, in 2009 and 2011. From 2004 to 2006, he worked as a Systems Engineer at Asea Brown Boveri (ABB), Uruguay. During the 2013 academic year, he was a visiting scholar with the Computer Science Department at Carnegie Mellon University. Since 2014, he has been an Assistant Professor with the Department of Electrical and Computer Engineering at the University of Rochester, Rochester, NY. His research interests lie in the areas of statistical learning from Big Data, network science, wireless communications, and signal processing. His current research focuses on algorithms, analysis, and application of statistical signal processing tools to dynamic network health monitoring, social, power grid, and Big Data analytics. Since 2012, he serves on the Editorial Board of the EURASIP Journal on Advances in Signal Processing. He received the Best Student Paper Award at the 13th IEEE Workshop on Signal Processing Advances in Wireless Communications, 2012 held at Cesme, Turkey, and was also a finalist of the Student Paper Contest at the 14th IEEE DSP Workshop, 2011 held at Sedona, Arizona, USA. His doctoral work has been recognized with the 2013 UofM's Best Dissertation Award (Honorable Mention) across all Physical Sciences and Engineering areas.