Keynote Addresses




Professor Peter Groumpos

University of Patras, Patra, Greece

Born in Greece in 1950. Educated at USA receiving the following degrees from the SUNY at Buffalo all in EE.:  B.Sc. in 1974, a M.Sc. in 1976 and the PhD in 1978. While studying at the undergraduate and Master level he had to work at the same time to earn his living.  Faculty member at the Dep. of Electrical and Computer Engineering at Cleveland State University 1979-1989. Returned to his motherland, Greece as a Full Professor, Dept. of Electrical and Computer Engineering, University of Patras 1989 till 2018. Presently he is an Emeritus professor. He established and developed the Laboratory for Automation and Robotics in 1992 and served as its Director till Sept 2018. He served as a chairman of the Department of ECE in the period 1993 – 2003. A Fulbright Scholar 1997-78, visited the University of Patras in which he taught and perform research in the area of Systems and Control. His main research interests are: Modelling and Controlling Complex Dynamic Systems (CDS), Intelligent Control, Soft-computing techniques for CDS, Fuzzy Cognitive Maps (FCM), Cognitive Control, Knowledge Management, Simulation and Application of Informatics in the areas: Business, Economics, Health, Agriculture, Industry, Environment, International Relations and Social Studies.  He has many publications (total of 350: books, editing books, invited chapters, plenary papers, conferences and workshops) with more than 5400 citations on his research results. He has been Plenary-Keynote speaker on more than 20 international conferences the last 10 years.

Artificial Intelligence for Business Intelligence

No surprise that there is not one definition of Artificial Intelligence (AI) been accepted by all. AI is the study of how to make computers do things at which, at the moment, people are better. Or AI is the simulation of human intelligence processes by machines, especially computer systems. In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.  In this plenary presentation an effort is made to see how AI is related and affecting Business Intelligence (BI). BI is a technology-driven process for analyzing data and presenting actionable information “intelligently” (to be defined) which helps executives, managers and other corporate end users make informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against that data and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers. And all these on an intelligent way. Overall, the role of BI is to improve all parts of a company by improving access to the firm's data and then using that data to increase profitability. Companies that employ BI practices can translate their collected data into insights of their business processes. The insights can then be used to create strategic business decisions that improve productivity, increase revenue and accelerate growth. To achieve these goals methods and techniques from AI and Intelligent Control (IC) need to be utilized and properly used. However there must be made clear that AI and BI are two different scientific areas. In this plenary talk the differences between them will be analyzed. The different goals and objectives of each scientific area will be considered and properly discussed. Companies like Microsoft, Oracle, and Tableau have developed BI tools for a range of business functions, including HR, sales, and marketing. By monitoring everything a business does on a daily basis – and utilizing data to create spreadsheets, performance metrics, dashboards, charts, graphs, and other useful visualizations – businesses can organize data and make traditionally difficult decisions much more easily. The adoption of BI solutions has grown nearly 50 percent in the past three years.


Dr. Andreas S. Maniatis
Entrepreneur, Commercial Manager, and Head of Analytics
CyberStream Ltd

Dr. Andreas Maniatis has been an active member of the Greek ICT industry for more than twenty-five years. Today he is a partner and Commercial Director at CyberStream LTD, a leading systems integrator and software manufacturer of state-of-the-art tools and solutions. He also serves as Head of the Business Intelligence – Visual Analytics Unit of the company, the later being the appointed reseller for the TIBCO Spotfire Visual Analytics Platform.Dr. Maniatis has participated in various projects in both the Public and the Private Sectors, where he has held positions ranging from developer to project manager to senior IT strategy consultant to team manager. He has also collaborated with the National Technical University of Athens and the General Secretariat of Research and Technology in many R&D programs in the European community. He is actively tutoring courses on Big Data Visualization and Analytics in numerous Academic Institutions.Dr. Maniatis holds a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens and an MSc from the same institution. His domains of interest include Software Lifecycle Management, Data Warehouses and OLAP, Data Mining and Decision Support Systems, Data Science and Artificial Intelligence, with specialization in the Visual Representation and the online, Interactive Exploration and Analysis of very large data sets (Visual Analytics and Big Data). He has published numerous papers in prestigious scientific journals and international conferences. 

Why do we Visualize? Paradigms from Exploratory Data Analysis (EDA), Data Journalism, and Artificial Intelligence (AI)

We, Homo Sapiens, are by gene coding a visual biological species. Vision is by far our most important sense, and has thus helped us dominate the planet.But what does the phrase “Data Visualization” sound like to the uninitiated? “Data” conjures up images of computers and statistical analysis, whereas Visualization is more accessible but vague enough so as to be unclear. One may wonder: Is Data Visualization new, overflowing with cutting edge tools and technology, or is it as old as human communication itself? Well, Data Visualization may be rooted in ancient times and have a rich history over the last couple centuries, but the field is transforming in the technological age, and transforming the world along with it. Big Data Analytics and Artificial Intelligence, along with Machine Learning and Deep Learning, have become the major scientific and technological catalysts that have successfully set in commotion a whole world of new, relative applications.

So, we Visualize, because:

  • Visualization is the most secure path towards achieving true Business and Organizational Intelligence, both in terms of entrepreneurship, as well as of technology,
  • Story-telling, Narration, and Comprehension are greatly augmented when Visuals are included and are wisely and carefully used, and finally,
  • Data Visualization has been a tremendously successful tool supporting Exploratory Data Analysis (EDA) at all levels, thus promoting the analysis and understanding of data in every single domain and area of application.

But despite the fact that the three pillars mentioned above form a more or less expected and straightforward path towards understanding and interpreting data, using them in various everyday applications (ranging from simple sales reports to autonomous car driving) is anything but trivial. We will herein work with history, reference examples and case studies that will help us adopt a recommended Data Visualization process.



Professor Thanos Kriemadis

Univesity of Peloponnese, Greece

Thanos Kriemadis is Professor teaching Total Quality Management and Strategic management at the University of Peloponnese.  He received his M.A., Ph.D., and M.B.A. from USA Universities. He was specialized in Strategic Management under the guidance of Dr. Ansoff (The Father of Strategic Management).  He was also an active member of the San Diego Deming User Group where he was introduced to Total Quality Management by Dr. Deming’s disciples. Dr. Kriemadis is Quality Auditor for Quality Management Systems (ISO 9001:2008) as well as Quality Assessor of the EFQM Excellence Award promoted by the European Foundation for Quality Management (EFQM) specialized in Small and Medium Enterprises and the Public sector-Education. Before moving to academia Dr. Kriemadis held several management posts in both the public and private sectors in the USA and Greece. In USA, he worked in the Quality Assurance Department of Motorola, Inc. using the six-sigma methodology.  He also served as a quality and strategy consultant developing and auditing quality systems and strategic plans in Greece, European Union and USA. Research interests include Total Quality Management and Strategic Management issues applied in service organizations.  

Benchmarking: A powerful tool of Business Intelligence for continuous organizational improvement

Business Intelligence (BI) is a set of technologies, methodologies, processes, and practices for gathering, storing, analysing, and providing access to data and business information, with the purpose to assist managers in decision-making at strategic, tactical and operational level (e.g. to identify new business opportunities, areas for improvement – inefficient business processes, cut costs, etc.). BI can improve quality, productivity and competitiveness of contemporary businesses. Benchmarking is a powerful tool of BI. It is the process of comparing Key Performance Indicators (KPIs) and business processes to main competitors, best-in-class business, and industry standards. It is the search for new best practices that lead to outstanding performance. The term best practices, according to Evans and Lindsay (2008), refer to methodologies that generate exceptional outcomes. A review of Benchmarking literature reveals that there is a great number of Benchmarking process models. The Benchmarking process developed by AT&T as well as by Chang and Kelly (1994) will be presented and analysed in depth. Competitive benchmarking, process benchmarking, and strategic benchmarking will also be discussed in detail.


Andrée PIECQ

Directrice scientifique de l’Institut Indépendant de Systémique des organisations (G.I.R.O.S)

Présidente d’honneur de l’asbl Systèmes & Organisations (S&O)

2019: General Secretary of the EUS-UES - Scientific Director of G.I.R.O.S – Honorary president of S&O Belgium - Member of the « Bertalanffy Center for the Study of Systems Science » (BCSSS)

From 2014 until today: systemic teacher at the Open University of Charleroi

From 2000 until today: creation of G.I.R.O.S. - Independent Institute of Systemic applied to Organizations – development of training, interventions, supervisions and research activities

From 1990 until 1999: elaboration of the first courses of systemic at the Ergology school of Brussels

From 1989 until 1999: Supervisor for psychologists at the French Community; speaker in education at the FUB in the 3rd special systemic cycle; development of a systemic model of school intercultural mediation with the FUB.

1982 graduated from the systemic interventions on human systems (CUL)1971 Master degree at the FUB Psychology in Etiology and Clinical Psychology.
Main publication, in 2011  «De la pensée systémique à la pratique de l’organisation le “giroscope” », Paris, L’Harmattan. »

ONCE UPON A TIME…THE BURNOUT - A systemic vision on Burnout 

Generally "burnout" is considered as a workers' illness. This psychosocial disorder is caused by a physical or mental suffering.  All psychosocial disorders conduct to absenteeism, but in the case of Burnout, this absenteeism is often extremely long and can sometimes last for years. The costs of it are thus enormous. 

This presentation offers an analysis that does not focus directly on workers. It considers absenteeism as a symptom on its own. This symptom shows that the company’s functioning is not optimal. Thereby there is a high risk that psychosocial disorders such as burnout emerges.This analysis uses a systemic model, called the "Giroscope”.  Like the real gyroscope, it indicates the direction to follow. 

In this presentation the model is used to diagnose the functioning of companies in order to ensure its sustainability. It starts from the analysis of 12 systemic concepts called "guiding principles of systems": systems/subsystems, members, boundaries, rules, finality, information broadcast, information reception, totality, circularity, feedback, homeostasis, "equifinality".They interact with each other’s and help diagnose the functioning of the company.Thanks to the gyroscope, strategies can be developed in order to prevent or to correct all psychosocial disorders, including burnout.