Prof. Karim Baïna
Mohammed V University in Rabat, Morocco
Prof. Karim Baïna is full Professor, Dean of Software
Engineering Department at ENSIAS (Ecole Nationale Supérieure
d’Informatique et d’Analyse des Systèmes), Mohammed V University in
Rabat, Morocco, since 2004. He is IBM MEA University Instructor (Trainer
of Trainees) on IBM Big Data Technologies, and has prepared to IBM Big
Data certification hundreds of faculty members, and students in Morocco,
Tunisia, and South Africa between 2015 and 2019.
He has obtained many Instructor certifications « Big Data Engineer - Mastery Award for Educators 2018 - 2010 », « IBM Artificial Intelligence Analyst - Mastery Award 2019 », « Data Scientist - Instructor Award for Educators 2017 - 2019 », « IBM Big Data Developer Mastery Award Certificate », and « IBM Big Data Specialist Certificate ».
He has been and Cooperation Service Responsible at ENSIAS leading international student exchanges with ENSIMAG/INPG (co-graduation) and ISIMA/UBP (co-graduation), ENSEIRB-Matematica/INPB, ENSEEIHT/INPT, ENSI/Tunisia, DSV/Stockholm Uni Sweden, Aalto Finland, and Sherbrooke Canada). He has been Leader of Alqualsadi research team (Enterprise Architecture, Quality of their Development and Integration) in EA (Enterprise Architecture), SOA (Service Oriented Architecture), BPM (Business Process Management), and BPI (Business Process Intelligence). He has achieved multiple consulting and training projects in Morocco, Tunisia, France, Australia, Sweden, Italy, and Cameroon. He has participated, managed, and coached many important companies IT projects from pre-sales, design to production for telco industry. He has been active operational and management member in many EU, Tempus, and DaaD (Deutscher Akademischer Austauschdienst), and SRC (Swedish Research Council) projects : MEDFORIST, MED-NETU, MED-IST, JOIN-MED, MENA, OPEN1-2&3, PORFIRE. He has more than 90 international publications, and he has served more than 20 times as invited speaker in international conferences. He has been more than ten times invited professor at international universities. He has defended his research habilitation (docent) at EMI (Ecole Mohammadia d'Ingénieurs), Mohammed V University Rabat, Morocco, in 2007. He has obtained his PhD thesis in Computer Science from UHP (Université Henri Poincaré), Nancy 1, France, in 2003, after what he has achieved his potdoctoral project in UNSW (University of New Soth Wales), Sydney, Australia. He has obtained his engineering degree in Computer Science and Applied Mathematics from ENSIMAG (Ecole Nationale Supérieure d’Information et Mathématiques Appliquées), Grenoble, France in 1999.
Prof. Orlando Belo
University of Minho, Portugal
Orlando Belo (www.di.uminho.pt/~omb) is Associate
Professor, with Habilitation, in the Department of Informatics at
University of Minho, Portugal. He is a member of the Department of
Informatics at University of Minho since 1986, and a member of the
ALGORITMI R&D Centre, at the same university, working in Business
Intelligence and Business Analytics, with particular emphasis in areas
involving Databases, Data Warehousing Systems, Data Analysis, and Data
During the last few years he was involved with several projects in the decision support systems area designing and implementing computational platforms for specific applications, such as fraud detection and control in telecommunication systems, data quality evaluation, and ETL systems for industrial data warehousing systems. He received a 5-year degree in Systems and Informatics Engineering in 1986, done “Provas de Aptidão Pedagógica e Capacidade Científica” (MSc equivalent) in 1991 in Expert Systems, finished its Ph.D. thesis in Multi-Agent System in 1998 in the Department of Informatics at University of Minho, and got his Habilitation in 2013 in Data Warehousing Systems. He published several scientific works, most of them in international conferences with peer reviewing, related to his main researching areas, with particular emphasis in Business Intelligence, Business Analytics, Data Warehousing Systems, On-Line Analytical Processing, and Data Mining applications.
Topic: A perspective about Graph Analytics:
from conventional to multidimensional data analysis
Abstract: In recent years, the emergence of applications generating and manipulating large volumes of data was enormous. In large part, this was due to social networks, which created very diverse and relevant needs for analysis, with a significant growth and permanent utilization. Aware of the importance and value of the data their networks produce, social network managers persistently require to their analysts useful, up-to-date and relevant information for supporting their decision-making activities - this information has to be extracted, in due time, from the extraordinary amount of data acquired in user interaction processes with the social networks they are managing. The establishment of network users’ usage and influence patterns is something quite crucial for the evolution of the network itself and, consequently, for its own success. These patterns are extremely helpful for enabling network managers to establish potential targets for triggering marketing actions, identifying fraud situations, developing crime prevention measures, or establishing new quality standards based on user preferences, just to name a few. In the design and development of this very intensive data analysis processes, many analysts choose to use one of the most exciting and long-standing structures for modelling and supporting data of their analytical processes: graphs. Graphs are very simple structures, quite easy to understand and use. Its potential for application in large data analysis processes is enormous. We can use them for solving problems of path analysis, connectivity or centrality, in many application domains, with great effectiveness. Today, due to the existence of large number of tools, especially oriented for graph data analysis, its application is quite easy. In this lecture, we will discuss the use of graphs in data analysis processes, starting with a brief exposition of their theory, concepts and basic manipulation operations, to their use in large databases supporting intensive data analysis processes, giving a particular emphasis to its application in multidimensional database systems.
Prof. Hassan Bevrani
University of Kurdistan, Iran
Professor Hassan Bevrani received PhD degree in electrical engineering from Osaka University, Osaka, Japan, in 2004. From 2004 up to now, he has worked as a post-doctoral fellow, senior research fellow, visiting professor, and professor with Osaka University, Kumamoto University, Queensland University of Technology (Australia), Kyushu Institute of Technology, Ecole centrale de Lille (France), and University of Kurdistan (Iran). He is the author of 5 international books, 15 book chapters, and more than 200 journal/conference papers. His current research interests include microgrid control, smart grid operation and control, and intelligent/robust control applications in power electric industry.