Pr. Michele Zorzi was born in Venice, Italy, on December 6th, 1966. He received the Laurea Degree and the Ph.D. in Electrical Engineering from the University of Padova, Italy, in 1990 and 1994, respectively. During the Academic Year 1992/93, he was on leave at the University of California, San Diego (UCSD), attending graduate courses and doing research on multiple access in mobile radio networks. In 1993, he joined the faculty of the Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy. After spending three years with the Center for Wireless Communications at UCSD, in 1998 he joined the School of Engineering of the University of Ferrara, Italy, where he became a Professor in 2000. Since November 2003, he has been on the faculty at the Information Engineering Department of the University of Padova. His present research interests include performance evaluation in mobile communications systems, random access in mobile radio networks, ad hoc and sensor networks, energy constrained communications protocols, and broadband wireless access.
Dr. Zorzi was the Editor-In-Chief of the IEEE Wireless Communications Magazine in 2003--2005, is currently the Editor-In-Chief of the IEEE Transactions on Communications, and serves on the Editorial Boards of the IEEE Transactions on Wireless Communications, the Wiley Journal of Wireless Communications and Mobile Computing and the ACM/URSI/Kluwer Journal of Wireless Networks. He was also guest editor for special issues in the IEEE Personal Communications Magazine ("Energy Management in Personal Communications Systems," Jun. 1998) and the IEEE Journal on Selected Areas in Communications ("Multi-media Network Radios," May 1999, and "Underwater Wireless Communications and Networks," to be published in 2008). He is a Fellow of the IEEE.
Synthetic molecular communication is an emerging research area offering many interesting and challenging new research problems for communication engineers, biologists, chemists, and physicists. Synthetic molecular communication is widely considered to be an attractive option for communication between nano-devices such as (possibly artificial) cells and nano-sensors. Possible applications of nano-communication networks include targeted drug delivery, health monitoring, environmental monitoring, and "bottom-up² manufacturing. The IEEE and ACM have recently founded several new conferences and journals dedicated to this exciting new and fast growing research area.
In this keynote, we will give first a general overview of the areas of synthetic molecular communication and nano-networking. Components of synthetic molecular communication networks, possible applications, and the evolution of the field will be reviewed. Subsequently, we will give an introduction to various synthetic molecular communication strategies such as gap junctions, molecular motors, and diffusion based molecular communication. Thereby, we will focus particularly on diffusion based synthetic molecular communication, identify the relevant basic laws of physics and discuss their implications for communication system design. One particular challenge in the design of diffusive synthetic molecular communication systems is intersymbol interference. We will discuss corresponding mitigation techniques and provide some results. Furthermore, we will present several receiver design options for diffusive synthetic molecular communication, discuss their respective advantages and disadvantages, and elaborate on the impact of external phenomena such as molecule degradation and flow. In the last part of the talk, we will discuss some research challenges in synthetic molecular communication from a communication and networking point of view.
Robert Schober received the Diplom (Univ.) and the Ph.D. degrees in electrical engineering from Friedrich-Alexander University Erlangen-Nuremberg (FAU), Germany, in 1997 and 2000, respectively. From May 2001 to April 2002 he was a Postdoctoral Fellow at the University of Toronto, Canada, sponsored by the German Academic Exchange Service (DAAD). From 2002 to 2011, he was a Professor and Canada Research Chair at the University of British Columbia (UBC), Vancouver, Canada. Since January 2012 he is an Alexander von Humboldt Professor and the Chair for Digital Communication at FAU. His research interests fall into the broad areas of Communication Theory, Wireless Communications, and Statistical Signal Processing.
Robert received several awards for his work including the 2007 Wilhelm Friedrich Bessel Research Award of the Alexander von Humboldt Foundation, the 2008 Charles McDowell Award for Excellence in Research from UBC, a 2011 Alexander von Humboldt Professorship, a 2012 NSERC E.W.R. Stacie Fellowship, and the 2017 Wireless Communication Technical Committee Recognition Award. In addition, he has received several best paper awards for his research and is listed as a 2017 Highly Cited Researcher by the Web of Science. Robert is a Fellow of the Canadian Academy of Engineering,a Fellow of the Engineering Institute of Canada, and a Fellow of the IEEE. From 2012 to 2015, he served as Editor-in-Chief of the IEEE Transactions on Communications. Currently, he is the Chair of the Steering Committee of the IEEE Transactions on Molecular, Biological and Multiscale Communication and serves on the Editorial Board of the Proceedings of the IEEE. Furthermore, he is a Member at Large of the Board of Governors and a Distinguished Lecturer of the IEEE Communications Society.
Artificial Intelligence (AI) can be defined in many ways, but one thing all experts agree upon is the key role machine learning plays in AI. This keynote will adopt a tutorial style to first provide a quick overview of the current state of AI and reviews in some details the main approaches followed in machine learning, with a special focus on the more recent advances in deep learning and neural networks. We will also present a hierarchical layered approach that exploits many types of sensor and non-sensor signals and data, and proposes suitable representations, as well as processing and analysis algorithms in order to apply machine learning, including deep and shallow learning. The framework can be explored in various decision-making environments, including healthcare and wellbeing, surveillance, and media and entertainment to mention a few fields.
MONCEF GABBOUJ received his BS degree in electrical engineering in 1985 from Oklahoma State University, Stillwater, and his MS and PhD degrees in electrical engineering from Purdue University, West Lafayette, Indiana, in 1986 and 1989, respectively.
Dr. Gabbouj is a Professor of Signal Processing at the Department of Signal Processing, Tampere University of Technology, Tampere, Finland, where he leads the Multimedia Research Group. Dr. Gabbouj held the prestigious post of Academy Professor with the Academy of Finland 2011-2015. He held several visiting professorships at different universities, including The Hong Kong University of Science and Technology, Hong Kong (2012-2013), Purdue University, West Lafayette, Indiana, USA (August-December 2011), the University of Southern California (January-June 2012), and the American University of Sharjah, UAE, (2007-2008). He was Head of the Department during 2002-2007, and served as Senior Research Fellow of the Academy of Finland in 1997-1998 and 2007-2008. His research interests include multimedia content-based analysis, indexing and retrieval, machine learning, nonlinear signal and image processing and analysis, voice conversion, and video processing and coding.
Dr. Gabbouj is a Fellow of the IEEE, a member of the European Academy and the Finnish Academy of Science and Letters. He is the past Chairman of the DSP Technical Committee of the IEEE Circuits and Systems Society and member of the IEEE Fourier Award for Signal Processing Committee. He was Honorary Guest Professor of Jilin University, China (2005-2010). He served as associate editor of the IEEE Transactions on Image Processing, and was guest editor of Multimedia Tools and Applications, the European journal Applied Signal Processing. He is the past chairman of the IEEE Finland Section, the IEEE Circuits and Systems Society, Technical Committee on Digital Signal Processing, and the IEEE SP/CAS Finland Chapter. He was also (co-)Chairman of BigDataSE 2015, EUVIP 2014, CBMI 2005, and WIAMIS 2001.
Technical solutions have recently been proposed to significantly improve the performance of wireless networks in terms of data rate, latency, reliability and energy efficiency. Many of these are being investigated by both academic and industrial institutions. In this talk, I will argue that most of these technical solutions can be categorised in only four technological trends, which are: i) bringing the network closer to the user, mainly through network densification, flying base stations, and massive MIMO, ii) bringing the content closer to the users, through caching popular content at the edge of the network, iii) exploiting higher frequency bands, and in particular millimetre wave frequencies, and iv) virtualising the network functions, which can leverage machine learning to enable an automated real-time optimisation of the network. In this talk, the potential and challenges associated with each of the above technological trends will be discussed.
Mounir Ghogho received his PhD degree in 1997 from the National Polytechnic Institute of Toulouse, France. He was an EPSRC Research Fellow with the University of Strathclyde (Scotland), from Sept 1997 to Nov 2001. In December 2001, he joined the University of Leeds where he was promoted to full Professor in 2008. While still affiliated with the University of Leeds, he joined the International University of Rabat (UIR) in January 2010, where he is currently the Director of TICLab (ICT Research Laboratory) and Scientific Advisor to the President. He is a Fellow of IEEE, a recipient of the 2013 IBM Faculty Award, and a recipient of the 2000 UK Royal Academy of Engineering Research Fellowship. He is currently an associate editor of the IEEE Signal Processing Magazine and a member of the steering committee of the Transactions of Signal and Information Processing. In the past, he served as an Associate Editor of the IEEE Transactions on Signal Processing and IEEE Signal Processing Letters, a member of the IEEE Signal Processing Society SPCOM, SPTM and SAM Technical Committee. He chaired many conferences and workshops including the European SIgnal Processing conference Eusipco2013 and the IEEE workshop on Signal Processing for Advanced Wireless Communications SPAWC’2010. He is the Eurasip Liaison in Morocco.
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