Prof. Milos Manic, Virginia Commonwealth University, USA
Professor Milos Manic is conducting research and teaching in area of artificial intelligence applied to energy, human- machine interfacing, cyber security, and resilient intelligent control systems. He is a Professor with Computer Science Department and Director of Modern Heuristics Research Group at Virginia Commonwealth University. He has over 20 years of academic and industrial experience. As principal investigator he has completed over 30 research grants with the National Science Foundation, Dept. of Energy, Idaho National Laboratory, Dept. of Air Force, Fujitsu Laboratories of America, and Hewlett-Packard Prof. Manic has served as an IEEE Industrial Electronics Society (IES) Officer, is a member of various standing and technical committees and boards of this Society, and is a founder and past chair of Technical Committee on Resilience and Security in Industry. He is a General Chair of IEEE IECON 2018. He has authored or co-authored over 180 peer-reviewed publications and holds several U.S. patents.
Speech Title: The Future of Artificial Intelligence - The Age of Trustworthy and Explainable Intelligence
Abstract: Abstract: The "New Age" of Artificial Intelligence has arrived. Autonomous cars are driving on our streets. Appliances in our homes "talk" to us and "companion" robots "dressed" in many shapes and forms are moving into our homes. With ubiquitous AI around us, difficult questions of replicating sentience, emotion, and memory arise. How do you teach a computer to feel, love, or dream, or forget? Also, as enabling machines to think and learn, how do we ensure morality and ethics in their future decisions, the quality difficult to "encode"? How do we replicate something we do not understand? And ultimately, can AI explain itself and get us to trust it?
This talk will address some of these hard questions, illustrate some aspects of general intelligence and deep learning, and provide examples on how to improve trust and provide metrics on confidence in modeling of complex control systems.
Prof. Michele Della Ventura, 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).
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, Ireland, Japan, 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 several researches related to technology supported learning for dyslexic students, learning through the use of social media and handheld technologies in a CLIL classroom and technology supported student music analysis and composition.
He teaches Music Informatics in University courses at Music Academies and Conservatories and Musical Technologies in Music High Schools.
Speech title: Creating inspiring learning environments by means of digital technologies
Abstract: While observing the context of formal learning, as far as the personal and general use of the network technologies to access information and the Social Networks (SNs) are concerned, it is inevitable to acknowledge the scarcity of cases where such technologies are used in support of teaching & learning activities. The potentialities of this type of technologies reside in the very creation of not only a bridge between formal and informal learning contexts, but also, and above all, of a very intense integration. The technologies within an intentional planning by the teacher may promote the shared knowledge building, the interaction with the information content, but also the customization of thelearning paths and strategies and the active and also creative learning of the different disciplines.
Dr. Hui Yu, University of Portsmouth, the United Kingdom
Hui Yu is a Reader with University of Portsmouth. His main research interest lies in visual computing and big data analysis, particularly in understanding and sensing the visual world human related issues with semantic interpretation. It involves and develops knowledge and technologies in vision, machine learning, virtual reality, brain-computer interaction and robotics. Dr. Yu's research work has led to many awards and successful collaboration with worldwide institutions and industries. He has done many 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 many international research conferences and summer schools. He is also Associated Editor of IEEE Transactions on Human-Machine Systems journal and Neurocomputing journal.
Speech Title: Wild Facial Data Processing and Virtual Reality Application
Abstract: Human related analysis has been an active research field for its wide applications. With the advancement in sensing system and computing technologies, many methods have been explored for human motion analysis in the wild, especially human action, facial and gaze analysis. Although the majority of this research has been conducted on 2D images, there are a significantly increasing demands for static and dynamic 3D analysis due to the improved performance on capturing the various visual cues. In this talk we will address the recent techniques in 2D/3D sensing systems, recognition and virtual reality application development. And the challenges of this research field will also be addressed.