Invited Speakers

Professor Mohamed NAJIM, ENSEIRB, Bordeaux, France

A Cruise Through Signal Processing Discipline

The IEEE Signal Processing Society is about 70 years old. Our discipline raised in Europe and in this country in the mid ’70. During this cruise I will provide with some inputs about its development and some souvenirsI shared with exceptional scholars I had the chance to meet during my career all over the word. I will pay attention to some pioneering works and their crossing road with control, maths and image processing. Finally I will provide with some examples of works I have carried on and some concluding remarks.

Mohamed Najim born in Morocco, 1945, has received his Doctorat d’Etat in Toulouse (1972). He spent 16 years in the Rabat University where he set up a laboratory rooted in the Moroccan economy. He created the ENSIAS the first engineering school in computer science in Africa. In 1988 he held the first chair in Signal and Image Processing created in Bordeaux and established partnership with Total, SAFRAN, Thales, CEA…He leaded consortia within the European Framework Programs. He authored 8 books and more than 200 papers. His previous Ph D students are enrolled in more than 10 countries. He lectured in all the continents.

Since 1988 he is an IEEE Fellow member and currently a Live Fellow member. He got the A. Shuman Prize Award in 1982, the TWAS Academy engineering prize, 2011, and the highest Award of the EURASIP Society (EURopean Association of Signal and Image Processing in 2013. Since 2000 he was decorated the highest distinction of the Kingdom of Morocco.He received the French distinction Palmes Académiques in 2016. He is currently an emeritus Professor.

Professor Chafik SAMIR, University of Clermont Auvergne, France

Abstract:

Advances in technology have led to an increased need for statistical methods, which are used in many applications including medical. When dealing with spatio-temporal shapes, most current methods are applied in a cross-sectional manner, i.e., they ignore any temporal structure contained in data sequences and deal only with the static spatial information. The development of techniques for spatio-temporal tracking and deformation would enable one to capture the local shape and temporal variabilities under a unified framework. A Spatio-temporal framework will construct a statistical model to account for the cross-sectional geometric variability of object shapes, and the additional functional dynamics. In medical imaging, such models can assist physicians in the interpretation of image sequences, e.g., they can be used to guide disease characterization via image sequence classification.

Professor Chafik Samir is an Associate Professor at CNRS Laboratoire d’Informatique, de Modélisation et d’Optimisation des Systèmes (LIMOS),  University of Clermont Auvergne (UCA), France. He obtained his Ph.D. degree in Computer Vision from Lille 1 University of Science and Technology in 2007. After spending two years as a post-doc at UCL, he joined UCA as an Assistant Professor in 2009. His main research interests involve fitting curves and optimization on Riemannian manifolds, statistical shape analysis of curves and surfaces, machine learning, computer vision, and their applications to real-world problems. In particular, he has been working modeling and simulation of shape variations and dynamics in medical studies.

Basel SOLAIMAN, Pr., Head of Image & Information Processing Dept., Institut Mines-Telecom
de l’Atlantique, Brest, France

Possibilistic Reasoning for Medical and Remote Sensing Scene Interpretation

Scene interpretation is a huge challenging research topic with applications in different domains: Military, Medical, Remote Sensing, Robotics, Underwater, Drone Systems, Intelligent Transportation, etc. Moreover, scene interpretation is an interdisciplinary endeavor
that draws upon expertise in computer vision, image processing, image understanding, artificial intelligence, data mining, machine learning, pattern recognition, knowledge representation, Reasoning paradigms, etc. It aims at the “automatic” extraction of implicit
knowledge and semantically high-level meaningful information and knowledge from massive volumes of information like a raw-image, an image sequence or a large collection of images (i.e. image datasets). The main challenge is to reveal out how low-level pixel representation enclosed in a raw-image, or a large collection of images can be processed to discover, and extract, “hidden” high-level information and implicit knowledge. This conference intends, first, to give a close analysis and to propose a global knowledge representation framework
allowing to position different research issues related to scene interpretation. The application of the possibilistic approximate reason approach is then proposed through different medical and remote sensing concrete examples. A brief introduction to possibility theory is also given in order to follow the different proposed application examples.

Basel Solaiman, Ingénieur Télécom (Ecole Nationale Supérieure des Télécommunications, 83), Ph.D., et Habilitation à Diriger des recherches, 97 (Université de Rennes I). Chercheur du Laboratoire L.E.P (Phillips/France), Ingénieur Chef de Projet à l’Institut d’Informatique Industrielle/France jusqu’en 1991. Il est actuellement Professeur et Chef du Département Image et Traitement de l’Information à Télécom Bretagne. Il a publié plus de 200 articles
scientifiques, trois livres académiques et a assumé plusieurs postes de responsabilités au sein de la société IEEE.

Basel Solaiman is professor and head of the image and information department at Ecole National Superieure des Telecommunications de Bretagne, Brest, France. Bassel Solaiman, received the telecommunication engineering degree from Ecole Nationale Supérieure des télécommunications de Bretagne (Télécom Bretagne). Brest, France, in 1983 and the PhD degree from the University de Rennes I, Brest, France, in 1989. He earned his HDR. from
Université de Rennes-I, France in 1997. From 1984 to 1985, he was a Research Assistant in the Communication Group at the Centre d’Etudes et de recherche Scientifique, Damascus, Syria. He joined the Image and Information Processing Department at Télécom Bretagne, Brest, France, in 1992. His current research interests include the fields of remote sensing, medical image processing, pattern recognition, neural network, and artificial intelligence.

Title: La sécurité dans le Web 2.0/3.0

ASIMI Ahmed is a full professor at the Faculty of Science, Agadir, Morocco. He received his Ph.D degree in Number theory from Department of Mathematics, Faculty of Science, University Mohammed V, Agdal in 2001, Morocco.

He is reviewer at the International Journal of Network Security (IJNS). His main areas of research interests include Number theory, Code theory, Computer Cryptology, Computer and Network Security.

 

Professor Taib SADIKI, UIR, Rabat Morocco
Title:
 La Localisation GNSS

Tayeb SADIKI  he is received his Computer Science Engineering degree from  Ecole Polytechnique Nice Sophia Antipolis, in 2003. He received his PhD degree from Eurecom, Sophia-Antipolis in Bayesian Adaptive Filtering in March 2007. He was Awarded paper at ASILOMAR, California 2006. From March  2007 to Jully 2011 he was a Project manager at AREVA TA France working on design of service-providing systems for telecommunication networks. In May 2008, he received the best price on hardware architecture for his system design at ESA, NL working on mobile location. Is currently an Associate Professor in Computer Science at
International University of Rabat.  His current research interests are Digital Signal Processing, Mobile location, GNSS, Hybridization, Adaptive Filtering, precoder design systems based on partial  channel state information, transceiver design in wireless. He is authored and co-authored for more than 60 papers and more than 15 atents.From March 2016, he was a President of raa-Tafilalet Foundation for Experts and Reacher’s. He is lso an expert at ACM and ESA.

Professor Mohammed BAKHOUYA, UIR, Rabat, Morocco

Title: Wireless Sensor Networks: Technologies and Applications

AbstractWireless Nano Sensor Networks (WNSNs) have been emerged as a typical sub-class of WSNs, but at nanoscale. The vision of WNSN could achieve the functionality and performance of today’s WSN applications with the exception that nodes are very tiny devices able to perform very simple computation, sensing and/or actuation tasks. In addition, nodes are assumed to be mobile and rapidly deployable. However, in order to develop WNSN applications and services, still many research issues have to be investigated. In this talk, we survey existing wireless ad hoc types and introduce WNSN as a future communication fabric for many emerging applications.

Mohamed BAKHOUYA is an associate professor at International University of Rabat. He obtained his HDR from UHA-France in 2013 and his PhD from UTBM-France in 2005. He has more than five years experiences in participating and working in sponsored ICT projects. He was PI of Aalto starting grant at Aalto University-Finland (2011-2013), Co-PI (UTBM side) of two European projects ASSET (Advanced Safety and Driver Support in Efficient Road Transport, FP7-SST, 2008-2011, and TELEFOT (Field Operational Tests of Aftermarket and Nomadic Devises in Vehicles, FP7-ICT, 2008-2012. He spent two years as a research scientist in US at George Washington University, HPC laboratory participating and working in sponsored projects, mainly UPC (Unified Parallel C) and NSF Center of High-performance and REConfigurable Computing.

Prof. Dr. Mostafa Ezziyyani, IEEE and ASTF Member received the “Licence en Informatique” degree, the “Diplôme de Cycle Supérieur en Informatique” degree and the PhD “Doctorat (1)” degree in Information System Engineering, respectively in 1994, 1996 and 1999 from Mahmmeed V University in Rabat, Morocco. Also, he received the second PhD degree “Doctorat (2)” in 2006, From Abdelmalek Essaadi University” in Distributed Systems and Web Technologies. In 2008 he receives a Researcher Professor Ability Grade. Now he is a professor of Computer Engineering and Information System in Faculty of Science and Technologies of Abdelmalek Essaadi University since 1996.

INTEGRATION OF BIG DATA ANALYTICS SOLUTION TO IMPROVE THE QoS OF NETWORKS FOR SMART DEVICES ADAPTATION

This talk aims to study, design and implement a solution as an intelligent system allowing the management of the contexts of a network, based on Big Data solutions in order to improve the quality of services related to the user devices. Thanks to knowledge of the network behavior by recovering the different contexts of the user, the operator will be able to better optimize the resources of the network, better meet the needs of the users, and offer them a service adapted to their needs closest to his expectations while minimizing operator costs. The main objective of this work is to optimize the network, to improve the quality of services and to identify the social behavior patterns used to initiate new income-generating activities and smart devices adaptation. This solution based on the BigData analytics solution using the advanced data mining algorithms. The process is divided into four parts, starting with network scanning and data storage, filtering/migrating of data gathering from networks, visualizing and controlling services and components and finally arriving at the mining stage as a decision support system for smart devices adaptation.

Pr. Ching-Hsien Hsu
Department of computer science,
Chung Hua University, Taiwan

Abstract:

This talk attempts to address a few critical issues, trends and opportunities on high performance computing in the cloud and big data era. Dr. Hsu will assess impacts of cloud and big data ecosystems on the development of high performance computing systems. The cloud & big data ecosystem includes the hardware and software infrastructure, new computing architectures, data center sustainability, and service models applied in supporting the emerging Big Data Intelligence and Internet of Things (IoT). In particular, a few enabling technologies, such as NoSQL, parallel data processing, energy efficient, load balancing, data locality and virtualization will be addressed.

About the Speaker:
Ching-Hsien Hsu , is a professor and the chairman in the department of computer science and information engineering at Chung Hua University, Taiwan; He was distinguished chair professor at Tianjin University of Technology, China, during 2012-2016. His research includes high performance computing, cloud computing, parallel and distributed systems, big data analytics. He has published 200 papers in top journals such as IEEE TPDS, IEEE TSC, ACM TOMM, IEEE TCC, IEEE TETC, IEEE System, IEEE Network, top conference proceedings, and book chapters in these areas. Dr. Hsu is the editor-in-chief of International Journal of Grid and High Performance Computing, and International Journal of Big Data Intelligence; and serving as editorial board for a number of prestigious journals, including IEEE Transactions on Service Computing, IEEE Transactions on Cloud Computing, International Journal of Communication Systems, International Journal of Computational Science. He has been acting as an author/co-author or an editor/co-editor of 10 books from Elsevier, Springer, IGI Global, World Scientific and McGraw-Hill. Dr. Hsu was awarded nine times distinguished award for excellence in research and annual outstanding research award through 2005 to 2016 from Chung Hua University; special talent award from Ministry of Education (2012-2015), and National Science Council (2010-2016), Taiwan. Since 2008, he has been serving as executive committee of IEEE Technical Committee of Scalable Computing; IEEE Special Technical Committee Cloud Computing; Taiwan Association of Cloud Computing. He is vice chair of IEEE Technical Committee on Cloud Computing, IEEE TCSC and IEEE senior member.

Professor Hany H. AMMAR, Engineering, West Virginia University, USA

Title: Cloud Computing, the Internet of Things
Abstract:

The evolution of Cloud Computing enabled the technology of the Internet of Things (IoT) which is described as the next technological revolution. IoT describes several technologies and research disciplines that enable the Internet to reach out into the real world of physical objects. Technologies like RFID, short-range wireless communications, real-time localization, and sensor networks are becoming increasingly pervasive, making the IoT a reality. This talk will describe the concepts of cloud computing and the IoT and their Islamic applications.

Prof. Ammar is a Professor of Computer Engineering in the Department of Computer Science and Electrical Engineering at West Virginia University. He has published over 150 articles in international journals and conference proceedings. Dr. Ammar is currently the Editor in Chief of the Communications of the Arab Computer Society On-Line Magazine, and he previously served as the Editor in Chief of the Journal of Computer Science and Engineering, in Arabic. He co-authored a book entitled Pattern-Oriented Analysis and Design: Composing Patterns to Design Software Systems published by Addison-Wesley, and a book entitled Software Engineering: Technical, Organizational and Economic Aspects, an Arabic Textbook, and co-edited the Proceedings of the Second International Conference on Computer Science Practice in Arabic, and the Proceedings of the Sixth International Computing Conference in Arabic. He was awarded a Fulbright Specialist Scholar Award in Information Technology funded by the US State Department – Bureau of Education and Cultural Affairs. He has been a Principal Investigator on a number of research projects funded by the Qatar National Research Fund (QNRF), the US National Aeronautics and Space Administration (NASA), the US National Science Foundation (NSF), and the US National Institute of Justice (NIJ). Dr. Ammar has been teaching in the areas of Software Engineering and Computer Architecture since 1987. His research interests are in Software Engineering and Identification Technologies.