Questions (and some answers) on L1 Subspace Signal Processing

On Monday November the 25th from 10 a.m. to 11 a.m.

Samovar organizes a talk of Prof. Dimitris A.Pados (University at Buffalo USA) in room G08

Abstract :

Subspace-based (L2-norm) algorithms have been lifeblood for the field of signal processing since its inception, with defining applications in detection and estimation (direction-of-arrival and frequency estimation, reduced-rank filtering and filter estimation, data dimensionality reduction, etc.). We will ask questions on L1 subspace signal processing. In particular, what is L1 subspace signal processing or –better said- how can it be defined? What does it do, what utility does it have? Why hasn’t it happened yet? In general, answers are hard to come. Some answers –few but important- will be provided, however. They feed optimism that a new line of L1 subspace signal processing is possible and modern outlier-resistant machine learning principles may be transferred under the well-developed umbrella of mainstream signal processing research.

Dimitris A. Pados was born in Athens, Greece, on October 22, 1966. He received the Diploma degree in computer science and engineering (five-year program) from the University of Patras, Greece, in 1989, and the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in 1994.

From 1994 to 1997, he held an Assistant Professor position in the Department of Electrical and Computer Engineering and the Center for Telecommunications Studies, University of Louisiana, Lafayette. Since August 1997, he has been with the Department of Electrical Engineering, State University of New York at Buffalo, where he is presently a Professor. He served the Department as Associate Chair in 2009-2010. Dr. Pados was elected three times University Faculty Senator (terms 2004-06, 2008-10, 2010-12), served on the Faculty Senate Executive Committee (2009-10) and serves on the University Budget Priorities Committee.

His research interests are in the general areas of communication theory and adaptive signal processing, with applications to interference channels and signal waveform design, secure wireless communications, cognitive radios and networks.

Dr. Pados is a member of the IEEE Signal Processing, Communications, Information Theory, and Computational Intelligence Societies. He served as an Associate Editor for the IEEE Signal Processing Letters (2001-2004) and the IEEE Transactions on Neural Networks (2001-2005). For articles that he coauthored with students, he received a 2001 IEEE ICT (Intern. Conf. on Telecomm.) best paper award, the 2003 IEEE TNN (Transactions on Neural Net.) Outstanding Paper Award, the 2010 IEEE ICC (Intern. Comm. Conf.) Best Paper Award in Signal Processing for Communications, and most recently the 2013 ISWCS (Intern. Symposium on Wireless Comm. Syst.) Best Paper Award in Physical Layer Communications and Signal Processing for the work “Some options for L1-subspace signal processing.” Professor Pados is a recipient of the 2009 SUNY-system-wide Chancellor’s Award for Excellence in Teaching and the 2011 University at Buffalo Exceptional Scholar – Sustained Achievement Award.

Contact : Monique Becker