WNCG Seminar Series: Sparse Sensing for Statistical Inference

Monday, November 16, 2015
UTA 7.532

Abstract: Ubiquitous sensors generate prohibitively large data sets. Large volumes of such data are nowadays generated by a variety of applications such as imaging platforms and mobile devices, surveillance cameras, social networks, power networks, to list a few. In this era of data deluge, it is of paramount importance to gather only the data that is informative for a specific task in order to limit the required sensing cost, as well as the related costs of storing, processing, or communicating the data. The main goal of this talk is therefore to present topics that transform classical sensing methods, often based on Nyquist-rate sampling, to more structured low-cost sparse sensing mechanisms designed for specific inference tasks, such as estimation, filtering, and detection. More specifically, we present fundamental tools to achieve the lowest sensing cost with a guaranteed performance for the task at hand. Applications can be found in the areas of radar, multi-antenna communications, remote sensing, and medical imaging.

 Seminar Slides



Delft University of Technology

Dr. Leus received his MS degree in Electrical Engineering and the PhD degree in Applied Sciences from the Katholieke Universiteit Leuven (KUL), Belgium, in June 1996 and May 2000, respectively. He has been a Research Assistant and a Postdoctoral Fellow at the KUL from October 1996 till September 2003. During the summer of 1998, he visited Stanford University (with Prof A. Paulraj), and from March 2001 till May 2002, he was a Visiting Researcher (with Prof. G. Giannakis) and Lecturer at the University of Minnesota. Currently, he is a Full Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology (TU Delft), The Netherlands.

Dr. Leus' research interests lie in the broad area of signal processing for communications and networking. Recently, he has been working on distributed signal processing for self organizing wireless networks, with applications in cognitive radio and sensor networks. The topics he addresses include energy efficiency, spectrum sensing, spectrum utilization and information processing.

He received numerous awards including a 2002 IEEE Signal Processing Society Young Author Best Paper Award and a 2005 IEEE Signal Processing Society Best Paper Award.

He is an IEEE Fellow (for contributions in Signal Processing for Communications) and the Editor in Chief of the EURASIP Journal on Advances in Signal Processing. In the past, he served as the Chair of the IEEE Signal Processing for Communications and Networking Technical Committee (SPCOM TC). He also served on the Editorial Board of the IEEE Transactions on Signal Processing, the IEEE Transactions on Wireless Communications, the IEEE Signal Processing Letters, and the EURASIP Journal on Advances in Signal Processing.