Quickest Detection of Correlation Structures in Networked Data...
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Title: Quickest Detection of Correlation Structures in Networked Data: Theory and Applications

Speaker: Ali Tajer 

Date/Time: Thursday, December 3, 9:40-10:30

Place: FENS 1040

Abstract: Driven by the advances in sensing and actuation, many physical systems are evolving towards networks of interconnected platforms in which large volume of data is constantly generated and processed. Correlation structures among the data streams generated by the agents in the network abstract their underlying interconnectivities and interactions. This has lead to recent studies on detecting correlation structures in networked-data. This talk will discuss data-adaptive correlation detection procedures, in which the network is observed only partially and sequentially, and evaluates their gains with respect to the commonly used approaches where observer affords observing the network with a full sample. As an application domain, we will discuss the application of this theory in agile detection and localization of power line outages in electricity.

Bio: Ali Tajer is an Assistant Professor of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute. During 2007-2010 he was with Columbia University where he received the M.A degree in Statistics and Ph.D. degree in Electrical Engineering, and during 2010-2012 he was with Princeton University as a Postdoctoral Research Associate. His research interests include mathematical statistics, statistical signal processing, and network information theory, with applications in wireless communications and power grids. Dr. Tajer Serves as an Editor for the IEEE Transactions on Communications, an Editor for the IEEE Transactions on Smart Grid, and as the Guest Editor-in-Chief for the IEEE Transactions on Smart Grid – Special Issue on Theory of Complex Systems with Applications to Smart Grid Operations.