Extracting insights and value from data through advanced analytics
In this talk, new and smart techniques are elaborated for enabling insights and extracting value from complex and large volumes of data, both coming from either business/organization/government level and individual level. I will show how big data and analytics can be exploited to support different domains of application from electronic commerce and understanding of customer behaviour to health. Besides the opportunities, pitfalls and risks of analytics techniques will be addressed.
Maria Fasli is a Professor, Director of the ESRC Business and Local Government Data Research Centre and Director of the Institute for Analytics and Data Science at the University of Essex. Educated in Greece (BSc Informatics 1996) and the UK (PhD Computer Science 2000), she has held positions at Essex since 1999. In 2005, she was awarded a National Teaching Fellowship by the HEA UK for her innovations in education. Between 2009-2014, she was Head of School of Computer Science and Electronic Engineering. In 2016, she was awarded a UNESCO Chair in Analytics and Data Science. Her research interests lie in artificial intelligence techniques for complex systems and analysing and modelling structured/unstructured data. Her research has been funded by Research Councils and other organisations and she has worked with a range of companies in data analytics related projects. She has published over 130 papers in the field of AI and data science and has delivered keynote talks at conferences.
Blockchain and applications in cloud: much more than cryptocurrencies
Blockchain and other distributed ledger technologies (DLTs) have recently emerged into the mainstream, demonstrating the advantages of decentralization, disintermediation, anonymity and censorship resistance, especially in relation with the financial sector. Blockchain technologies, through recent development, have not only enabled simple transactions, but also complex computation on a network where parties are geographically distant or have no particular trust in each other to interact and exchange value and information on a fully distributed basis with fewer to non-existent central intermediaries. Many popular applications are cloud related. These advances are now not just limited to the financial sector, but also new internet applications can harness these building blocks to empower users to take control of their online footprint, such as in healthcare, social media and other digital services. The IEEE Blockchain community shall become the gathering place for academic researchers, practitioners and business innovators alike, where they may meet and work together to embrace, promote and enhance blockchain technologies and their applications.
Prof. Chunming Rong is the co-chair of IEEE Blockchain, chair of IEEE Cloud Computing. He is the head of the Center for IP-based Service Innovation (CIPSI) at the University of Stavanger (UiS) and adjunct Chief Scientist leading Big-Data Initiative at IRIS. He was vice president (2015-2016) of CSA Norway Chapter. His research work focuses on data science, cloud computing, security and privacy. He is an IEEE senior member and is honoured as member of the Norwegian Academy of Technological Sciences (NTVA) since 2011. He has extensive contact network and projects in both the industry and academic. He is also founder and Steering Chair of IEEE CloudCom conference and workshop series. He is the steering chair and associate editor of the IEEE Transactions on Cloud Computing (TCC), and co-Editors-in-Chief of the Journal of Cloud Computing (ISSN: 2192-113X) by Springer. Prof. Rong has extensive experience in managing large-scale R&D projects funded by both industry and funding agencies, both in Norway and EU.
Different types of artificial intelligence: without learning mechanism and coupled to Big Data
He will explain the difference between these two AI, the first one without any learning mechanism and the second one based on the coupling Big Data and Machine Learning. He will illustrate this difference in board game playing, language translation and autonomous cars. Furtermore, he will then show how authors of the unconscious AI would like to rewrite all AI algorithms on the basis of this coupling.
Prof. Hugues Bersini is born the 19/1/61 and is living in Brussels. He has an MS degree (1983) and a Ph.D in engineering (1989) both from Université Libre de Bruxelles (ULB). After having been supported as a researcher by a EEC grant from the JRC-CEE in Ispra (1984-1987), he became member of the IRIDIA laboratory (the AI laboratory of ULB). He is now heading this same lab with Marco Dorigo. He is member of the belgium royal academy. Since 1992, he is full professor at ULB, teaching computer science, Web technology, business intelligence, programming and AI to university students (Solvay and Polytechnic Schools) and for industries. He has been partner of various industrial projects and EEC esprit projects involving the use of adaptive fuzzy or neuro controllers, optimisation algorithms and data mining. Over the last 20 years, he has published about 300 papers on his research work which covers the domains of cognitive sciences, AI for process control, connectionism, fuzzy control, lazy learning for modelling and control, reinforcement learning, biological networks, the use of neural nets for medical applications, frustration in complex systems, chaos, computational chemistry, object-oriented technologies, immune engineering and epistemology. He is quite often asked for giving tutorials covering the use of neural networks, object orientation and the behaviour of complex systems. He is a pionneer in the exploitation of biological metaphors (such as the immune system) for engineering and cognitive sciences. He is the author of fifteen french books covering basic computer sciences, artificial intelligence, complex systems and also two sets of novels dedicated to the technological future of the world. These last years, three spin-off have been created out of researchs done at IRIDIA: Cluepoints, Tevizz and In Silico DB.
Real-time clouds scheduling issues and challenges
Although for several years now there has been important research in cloud computing, there still remains a wide range of open challenges due to the heterogeneity of cloud resources and the characteristics of the applications executed on such platforms. Jobs are usually complex consisting of multiple component tasks, featuring different degrees of variability in their computational demands. Furthermore, complex multiple-task jobs may have precedence constraints and specific deadlines and may impose several restrictions and QoS requirements. Therefore, real-time applications can take advantage of intensive computing capabilities of clouds. One of the most important aspects in cloud computing is the effective scheduling of real-time complex parallel jobs, allowing for guarantees that the deadlines will be met. Furthermore, the energy efficiency of cloud systems is of paramount importance. However, to reduce the energy consumption while meeting deadlines, appropriate adaptive scheduling algorithms are required. In this talk we will present recent research covering a variety of concepts on real-time complex jobs scheduling in the cloud, and we will provide future research directions.
Helen Karatza is a Professor Emeritus in the Department of Informatics at the Aristotle University of Thessaloniki, Greece, where she teaches courses in the postgraduate and undergraduate level, and supervises doctoral and postdoctoral research. Dr. Karatza's research interests include Computer Systems Modeling and Simulation, Performance Evaluation, Grid and Cloud Computing, Energy Efficiency in Large Scale Distributed Systems, Resource Allocation and Scheduling and Real-time Distributed Systems. Dr. Karatza has authored or co-authored over 210 technical papers and book chapters including four papers that earned best paper awards at international conferences. She is senior member of IEEE, ACM and SCS, and she served as an elected member of the Board of Directors at Large of the Society for Modeling and Simulation International. She served as Chair and Keynote Speaker in International Conferences. Dr. Karatza is the Editor-in-Chief of the Elsevier Journal “Simulation Modeling Practice and Theory” and Senior Associate Editor of the “Journal of Systems and Software” of Elsevier. She was Editor-in-Chief of “Simulation Transactions of The Society for Modeling and Simulation International” and Associate Editor of “ACM Transactions on Modeling and Computer Simulation”. She served as Guest Editor of Special Issues in International Journals.