2022 8th International Conference on e-Society, e-Learning and e-Technologies

Keynote Speakers


Michele Della Ventura
Professor. Dr., Music Academy 'Studio Musica', Italy

Michele Della Ventura, professor of Music Technology, is a learning expert, researcher and instructional designer. His research interests include correlation between music and mathematics with a particular emphasis on artificial intelligence research in the field of computer-aided analysis of tonal music; intelligent systems; enhancing teaching and learning with technology; assessment for learning and strategies and models for the effective integration of technology into the curriculum at all academic levels.
He is the author of several articles presented at many conferences and published in international science magazines and high school textbooks (also featured at the International Book Salon of Turin in 2012 and 2018).
He proofreads articles and is a member of scientific committees in International Conferences.
He was invited as keynote speaker to International Conferences in Italy, Austria, Canada, China, Czech Republic, France, Germany, Hong Kong, Hungary, Ireland, Japan, Norway, Poland, Portugal, Romania, Singapore, Spain, UK, US (Baltimora, Boston, Las Vegas, New York, Washington).
Michele Della Ventura has also consulted on Big Data and Semantic Technology projects in Italy. Some of the projects include indexation of the symbolic level of musical text.
He is currently involved in a research project related to technology supported learning in collaboration whit Università di Roma La Sapienza.
He teaches Music Informatics in University courses at Music Academies and Conservatories and Musical Technologies in Music High Schools.

Speech Title: E-Teacher vs E-Student
Nowadays we find ourselves witnessing, not always adequately aware, of a great change, the one produced by digital media and the web. Hence the need for teachers to educate first of all themselves, if they want to guarantee a good education to students, that is, the most direct witnesses of this change. And this is possible not from outside but, as far as possible, from within the media. Only in this way does the teacher begin a learning process that leads him to discover new environments in which learning and teachings are presented as circular and interchangeable; roles have marked elements of flexibility; the learning materials are conceived as open and therefore constantly integrable and modifiable by all the actors (students, teachers, tutors); the environments take on various configurations, in order to the different activities that gradually emerge within the learning community; communications proceed according to multidirectional trends. In this talk we will address the challenges that teachers have to face in order to organize learning experiences and thus improve the learning process.


Hui Yu
Chair/Professor. Dr.,
University of Portsmouth, the United Kingdom

Dr. Hui Yu is a Chair/Professor with the University of Portsmouth in the UK. He is the Head of the Visual Computing Group at the university. His main research interest lies in visual computing and big data analysis, particularly in understanding and sensing the visual world of human related issues with semantic interpretation. It involves and develops knowledge and technologies in vision, machine learning, virtual reality, brain-computer interaction and robotics. Professor Yu's research work has led to many awards and successful collaboration with worldwide institutions and industries. He has led projects supported by EPSRC, ESRC, Royal Academy of Engineering, EU-FP7 and industries. He has extensive contributions to the international research community with organizing and chairing international research conferences and summer schools. He is also Associated Editor of IEEE Transactions on Human-Machine Systems journal and Neurocomputing journal.

Speech Title: Emotion Sensing for Social and Machine Interaction    
Abstract: With the increasing demand of machine intelligence across a wide range of application scenarios, human-machine interaction (HMI) emerges as another essential communication, whereby facial-expression-aware is one of the principal features for natural interaction. And it is also very useful for social interation training. The principal branch of my research was driven by these thoughts: combining knowledge of creative technologies with multiple disciplines, such as psychology, cognition, visual computing, computer graphics and machine learning. Particularly, biometric data precisely record the facial muscle activity or brain activity closely related to facial movements and the internal emotional states. These multiple sensing channels would help provide an insight into the emotion and perception of facial expression, to develop widely accessible HMI solutions able to track facial motions, and recognise affective states in a highly efficient and precise manner. This talk will discuss the development of visual facial data and electromyogram (EMG) processing for emotion detection with the application focusing on VR/AR.

Plenary Speaker


Prof. Dr. Thomas Hanne
University of Applied Sciences and Arts Northwestern Switzerland, Switzerland

Thomas Hanne received master's degrees in Economics and Computer Science, and a PhD in Economics. From 1999 to 2007 he worked at the Fraunhofer Institute for Industrial Mathematics (ITWM) as senior scientist. Since then he is Professor for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland and Head of the Competence Center Systems Engineering since 2012. Thomas Hanne is author of more than 160 journal articles, conference papers, and other publications and editor of several journals and special issues. His current research interests include computational intelligence, evolutionary algorithms, metaheuristics, optimization, simulation, multicriteria decision analysis, natural language processing, systems engineering, software development, logistics, and supply chain management.

Speech Title: On the Evolution of Multiobjective Evolutionary Algorithms
We provide a survey of the development history of multiobjective evolutionary algorithms as one of the major approaches in complex search and optimization problems. We first introduce some basic concepts related to multiobjective optimization and discuss basic types of multiobjective evolutionary algorithms. Pareto-based selection and niching are discussed in more details together with further advances in the development of respective algorithms. After that, applications are surveyed in two rather established areas, i.e., engineering and economics, and a more recent field, i.e., advanced analytics. We finish with the conclusions that compare the history of multiobjective evolutionary algorithms with an evolutionary process itself.