Sequential Estimation over Networks of Agents

Professor Petar M. Djuric, Stony Brook University

Wegmans Hall 1400

Abstract: We address the problem of decentralized state estimation in networks of agents. The agents are spatially distributed and acquire local measurements with information about a time-varying state described by some underlying state-space model. The agents aim at making inference about the time-varying state not only based on their measurements but also using information received from neighboring agents. This information can be local estimates of the state and/or measurements of these agents. We discuss ways of constructing the local estimates through such cooperation. We present strategies based on the concepts of diffusion and consensus.

Bio: Petar M. Djurić received the B.S. and M.S. degrees in electrical engineering from the University of Belgrade, respectively, and the Ph.D. degree in electrical engineering from the University of Rhode Island. He is a SUNY Distinguished Professor and currently a Chair of the Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA. His research has been in the area of signal and information processing with primary interests in the theory of signal modeling, detection, and estimation; signal and information processing over networks; machine learning; Monte Carlo-based methods; RFID and the IoT. Prof. Djurić was a recipient of the IEEE Signal Processing Magazine Best Paper Award in 2007 and the EURASIP Technical Achievement Award in 2012. In 2008, he was the Chair of Excellence of Universidad Carlos III de Madrid-Banco de Santander. From 2008 to 2009, he was a Distinguished Lecturer of the IEEE Signal Processing Society. He has been on numerous committees of the IEEE Signal Processing Society and of many professional conferences and workshops. He was the Editor-in-Chief of the IEEE Transactions on Signal and Information Processing over Networks. Prof. Djurić is a Fellow of IEEE and EURASIP.