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The problem of detecting abrupt changes or anomalies in stochastic systems and time series, often referred to as the quickest change detection (QCD) problem, arises in various branches of science and engineering. Applications include infrastructure monitoring, quality control engineering, intrusion detection in computer networks and security systems, detection of the onset of an epidemic, failure detection in manufacturing systems and large machines, biomedical signal and image processing and financial markets. The classical QCD problem is formulated as one where there is a sequence of observations whose distribution changes at an unknown time, and the goal is to detect the change as quickly as possible, subject to a false alarm constraint. In the first half of this talk, we provide a brief overview of the classical QCD problem and its solutions.
In many engineering applications of QCD, there may be a cost (e.g., energy) associated with acquiring observations. In the second half of the talk, we consider the QCD problem with an additional constraint on the cost of the observations used in the detection process, and we develop QCD algorithms that are data-efficient or energy-efficient. We demonstrate the working of one of these algorithms on a mote with a light sensor.
Prof. Veeravalli received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1992, the M.S. degree from Carnegie-Mellon University in 1987, and the B.Tech degree from Indian Institute of Technology, Bombay in 1985. He is currently a Professor in the department of Electrical and Computer Engineering (ECE) and the Coordinated Science Laboratory (CSL) at the University of Illinois at Urbana-Champaign. He was on the faculty of the School of ECE at Cornell University before he joined Illinois in 2000. He served as a program director for communications research at the U.S. National Science Foundation in Arlington, VA during 2003-2005. His research interests include distributed sensor systems and networks, wireless communications, detection and estimation theory, and information theory. He is a Fellow of the IEEE, and a recipient of the IEEE Browder J. Thompson Best Paper Award and the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE). He served as a distinguished lecturer for the IEEE Signal Processing Society during 2010-2011.