Princeton University

School of Engineering & Applied Science

Quickest Change Detection under Transient Dynamics

Venugopal V. Veeravalli, University of Illinois at Urbana-Champaign
B205 Engineering Quadrangle
Tuesday, November 21, 2017 - 4:30pm

The problem of detecting abrupt changes in stochastic systems and time series, often referred to as the quickest change detection (QCD) problem, arises in various branches of science and engineering. It is assumed that the observations of the system undergo a change in distribution in response to a change or disruption in the environment. The observations are obtained sequentially, and  if the state changes from the normal state, then it is of interest to detect this change as soon as possible, subject to false alarm constraints, and take any necessary action in response to the change. In the first part of this talk, an up-to-date overview of the results on the QCD problem will be provided. In the second part of the talk, the focus will be on an interesting variant of the QCD problem, where the change from the initial distribution to a final persistent distribution does not happen instantaneously, but after a series of cascading transient phases. We design an efficient algorithm for this QCD problem, and illustrate its application to the detection and isolation of line outages in power systems using phasor measurement unit (PMU) measurements.

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 (Silver Medal Honors) in 1985. He is currently the Henry Magnuski Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign, where he also holds appointments with the Department of Statistics, the Coordinated Science Laboratory (CSL) and the Information Trust Institute (ITI) 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 span the theoretical areas of detection and estimation, information theory, statistical learning, and stochastic control, with applications to data science, wireless communication systems and networks, sensor networks, and cyberphysical systems.  He is a Fellow of the IEEE. Among the awards he has received for research and teaching are the IEEE Browder J. Thompson Best Paper Award (1996), the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE) (1999), and the Abraham Wald Prize in Sequential Analysis (2016). He served as a distinguished lecturer for the IEEE Signal Processing Society during 2010-2011.
This seminar is supported with funds from the Korhammer Lecture Fund.