Prof. Abdelhak Zoubir (Technische Universität Darmstadt, Germany)
Short Bio : Abdelhak M Zoubir is a Fellow of the IEEE and an IEEE Distinguished Lecturer (Class 2010-2011). He received his Dr.-Ing. from Ruhr-Universität Bochum, Germany in 1992. He was with Queensland University of Technology, Australia from 1992-1998 where he was Associate Professor. In 1999, he joined Curtin University of Technology, Australia as a Professor of Telecommunications and was Interim Head of the School of Electrical & Computer Engineering from 2001 until 2003. In 2003, he moved to Technische Universität Darmstadt, Germany as Professor of Signal Processing and Head of the Signal Processing Group. His research interest lies in statistical methods for signal processing with emphasis on bootstrap techniques, robust detection and estimation and array processing applied to telecommunications, radar, sonar, car engine monitoring and biomedicine. He published over 400 journal and conference papers on these areas. Professor Zoubir was Technical Chair of the 11th IEEE Workshop on Statistical Signal Processing (SSP) in 2001, Technical Co-Chair of the 39th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in 2014, General Co-Chair of the 3rd IEEE International Symposium on Signal Processing & Information Technology (ISSPIT) in 2003, the 5th IEEE Workshop on Sensor Array and Multi-channel Signal Processing (SAM) in 2008, the 21st European Conference on Signal Processing (EUSIPCO) in 2013, and the 14th IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC) in 2013. He was an Associate Editor of the IEEE Transactions on Signal Processing from 1999-2005 and a Member of the Senior Editorial Board of the IEEE Journal on Selected Topics in Signal Processing from 2009-2011. He served on the Editorial Boards of the EURASIP journals Signal Processing and The Journal on Advances of Signal Processing (JASP). He was the Editor-In-Chief of the IEEE Signal Processing Magazine (2012-2014). Dr Zoubir was Past-Chair (2012) of the IEEE SPS Technical Committee Signal Processing Theory and Methods (SPTM) (Chair (2010-2011), Vice-Chair (2008-2009) and Member (2002-2007)) and was a Member of the IEEE SPS Technical Committee Sensor Array and Multi-channel Signal Processing (SAM) (2007-2012). He also served from 2009-2016 on the Board of Directors of the European Association of Signal Processing (EURASIP) whose president he currently is (2017-2018). He also was a member of the Board of Governors of the IEEE Signal Processing Society (2015-2017).
“Advances in Through-Wall Radar Imaging”
Abstract : Automatic detection of Humans and objects behind visually opaque materials is an extremely important task with numerous civilian and military applications. For example, in police and firefighter missions or search and rescue operations, one is interested in detecting buried survivors after an earthquake or detecting concealed weapons and explosives. Through-Wall Radar Imaging (TWRI) is an emerging technology with an enormous potential for applications such as the ones above and beyond. TWRI involves cross-disciplinary research in electromagnetic propagation, antenna and waveform design, wall compensation, and image and signal processing. The talk puts in perspective how to discern the presence of indoor targets and proposes effective methods for their discrimination and classification. The algorithms presented are not target or class of target specific, but rather applicable to a variety of targets, and are validated by experimental data. We will also discuss how Compressive Sensing (CS) can achieve various radar sensing goals and objectives, and how it compares with the use of full data volume. Different radar specifications and configurations will be used. In particular, we will address CS for urban radars towards achieving exploitation of multipath. All of the above issues will be examined using real data.
Waleed Ejaz, Ph.D., SMIEEE (Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada)
Short Bio : Waleed Ejaz (S’12, M’14, SM’16) is a Senior Research Fellow at the Department of Electrical and Computer Engineering, Ryerson University and Assistant Professor (PT) at the School of Applied Technology, Humber Institute of Technology, Toronto, Canada. Prior to this, he was a Post-doctoral fellow at Queen’s University, Kingston, Canada. He received his Ph.D. degree in Information and Communication Engineering from Sejong University, Republic of Korea. He earned his M.Sc. and B.Sc. degrees in Computer Engineering from National University of Sciences & Technology, Islamabad, Pakistan and University of Engineering & Technology, Taxila, Pakistan, respectively. He has experience working with top engineering universities as a Faculty Member. His current research interests include Internet of Things (IoT), energy harvesting, 5G cellular networks, and mobile cloud computing. He is currently serving as an Associate Editor of the IEEE Communications Magazine, IEEE Canadian Journal of Electrical and Computer Engineering, and the IEEE ACCESS. In addition, he is handling several special issues in prestigious journals. He also completed certificate courses on Teaching and Learning in Higher Education from the Chang School at Ryerson University. Dr. Ejaz is a registered Professional Engineer (P.Eng.) of the province of Ontario, Canada.
“Enabling Communication Technologies for Internet of Things”
Abstract : The Internet of Things (IoT) is expected to provide sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, etc. IoT applications demand diverse and wide range of requirements in terms of latency, reliability, energy efficiency, spectrum efficiency, etc. Therefore, IoT systems must have the ability to deal with the challenging requirements of both users and applications. The talk will provide a comprehensive overview of enabling communication technologies for IoT. The focus will be given to reconfigurable IoT systems and energy management for IoT. The most recent results will be analyzed to enhance performance of IoT systems in terms of increase system throughput, coverage, and energy efficiency. The talk will also discuss IoT applications include disaster management, smart homes, smart grid, and charging management for electric vehicles. Finally, the talk will present future challenges, with special focus on the challenges to support large number of devices, integration of wide range of heterogeneous sensor networks and technologies, as well as integration of context information and user experience in the IoT system.
Prof. Abdelhak Zoubir (Technische Universität Darmstadt, Germany)
“Advances in Array Processing”
Abstract : Antenna Array (Signal) Processing, or Sensor Array (Signal) Processing, or simply Array Processing deals with methods for processing the output data of an array of sensors, located at different points in space in a wavefield. Its objective is to get insight into the structure of the waves that carry information traversing the array. For example, one may be interested in the location parameters of a source or of the number of sources that impinge on the array. Array Processing is also concerned with the finding of the number of sources in the wavefield. Array Processing algorithms have matured over the last three decades and have become a state-of-the-art tool for solving challenging problems in diverse applications in engineering practice. Array Processing is more important than ever before with the increase of its wide-range applicability in advanced applications, including biomedicine and wireless communications. The tutorial is designed for researchers and practicing engineers who wish to equip themselves with foundations of sensor array signal processing, find out about the most recent research advances in the field, about new directions, and state-of-the-art applications. The tutorial is also suited for graduate students, interested in discovering the most challenging and recent trends in Array Processing so as to embark in a timely graduate education journey.