PLEASE NOTE: In view of the COVID-19 uncertainty, the dates for the Computing Conference 2020 may change. Please do not make any travel arrangements at this time.
PLEASE NOTE: In view of the COVID-19 uncertainty, the dates for the Computing Conference 2020 may change. Please do not make any travel arrangements at this time.

Keynote Speakers

Amir H. Gandomi (University of Technology Sydney)

Amir H. Gandomi is a Professor of Data Science at the Faculty of Engineering & Information Technology, University of Technology Sydney. Prior to joining UTS, Prof. Gandomi was an Assistant Professor at the School of Business, Stevens Institute of Technology, NJ and a distinguished research fellow in BEACON center, Michigan State University. Prof. Gandomi has published over one hundred and sixty journal papers and five books which collectively have been cited more than 12,500 times (h-index = 55). He has been named as Highly Cited Researcher (top 1%) for three consecutive years, 2017 to 2019, and ranked 19th in GP bibliography among more than 12,000 researchers. He has also served as associate editor, editor and guest editor in several prestigious journals and has delivered several keynote/invited talks. His research interests are global optimization and (big) data mining using machine learning and evolutionary computations in particular.

Keynote Title: Evolutionary Computation: Concepts and Key Applications

Abstract: Evolutionary computation (EC) techniques are a subset of artificial intelligence, but they are slightly different from the classical methods in the sense that the intelligence of EC comes from biological systems or nature in general. The efficiency of EC is due to their significant ability to imitate the best features of nature which have evolved by natural selection over millions of years. The main theme of this presentation is about EC techniques and their application to real-world problems. On this basis, the presentation is divided into two separate sections including (big) data mining, and global optimization. First, applied evolutionary computing in data mining field will be presented, and then their new advances will be mentioned such as big data mining. Here, some of my studies on big data mining and modelling using EC and genetic programming, in particular, will be presented. As case studies, EC application in some real-world problems will be introduced. And then, application of EC for response modelling of a complex engineering system under stochastic loads will be explained in detail to demonstrate the applicability of these algorithms on a complex real-world problem. In the second section, the evolutionary optimization algorithms and their key applications in the optimization of complex and nonlinear systems will be discussed. It will also be explained how such algorithms have been adopted to real-world problems and how their advantages over the classical optimization problems are used in action. Optimization results of large-scale systems using EC will be presented which show the applicability of EC. Some heuristics will be explained which are adaptable with EC and they can significantly improve their results.

Schahram Dustdar (TU Wien, Austria)

Schahram Dustdar is Full Professor of Computer Science heading the Research Division of Distributed Systems at the TU Wien, Austria. He holds several honorary positions: University of California (USC) Los Angeles; Monash University in Melbourne, Shanghai University, Macquarie University in Sydney, and University of Groningen (RuG), The Netherlands (2004-2010). From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA. From 1999 - 2007 he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by Engineering NetWorld AG), a venture capital co-funded software company focused on software for collaborative processes in teams. Caramba Labs was nominated for several (international and national) awards: World Technology Award in the category of Software (2001); Top-Startup companies in Austria (Cap Gemini Ernst & Young) (2002); MERCUR Innovation award of the Austrian Chamber of Commerece (2002). He is founding co-Editor-in-Chief of the new ACM Transactions on Internet of Things (ACM TIoT) as well as Editor-in-Chief of Computing (Springer). He is an Associate Editor of IEEE Transactions on Services Computing, IEEE Transactions on Cloud Computing, ACM Transactions on the Web, and ACM Transactions on Internet Technology, as well as on the editorial board of IEEE Internet Computing and IEEE Computer. Dustdar is recipient of the ACM Distinguished Scientist award (2009), the IBM Faculty Award (2012), the IEEE TCSVC Outstanding Leadership Award (2018), the IEEE TCSC Award for Excellence in Scalable Computing (2019). an elected member of the Academia Europaea: The Academy of Europe, where he is chairman of the Informatics Section, as well as an IEEE Fellow (2016).

Benedict du Boulay: (Emeritus Professor, University of Sussex)

Following a Bachelors degree in Physics at Imperial College London, he spent time both in industry and as a secondary school teacher before returning to university to complete his PhD in 1978 in the Department of Artificial Intelligence at the University of Edinburgh working on Logo. After a post-doc position at Edinburgh, a lectureship at the University of Aberdeen and a Sloan Fellowship at the University of California San Diego, he joined Sussex as a lecturer in 1983. He has been at Sussex since then, taking many roles of responsibility including Dean of Cognitive and Computing Sciences (COGS, 1994-1998) as well as Dean of Science and Technology (2002-2009). He has held two Erskine Fellowships at the University of Canterbury, New Zealand (2010, 2012) where he taught a course Artificial Intelligence in Education. He became an Emeritus Professor at the University of Sussex in 2010 and a visiting Professor at the London Knowledge Laboratory within University College London (UCL) in 2017. He has two main research areas. The first is the Psychology of Programming where his main work has been in the area of novices learning programming and the development of tools to assist that process. The second is the application of Artificial Intelligence in Education. Here he is particularly interested in issues around modelling and developing students’ metacognition and motivation. He has edited/written 11 books and written over 190 papers (including 56 journal papers) inthe areas indicated above. He has 3 invited commentary papers in the 2016 Anniversary Issue of the International Journal of Artificial Intelligence in Education celebrating his highly cited papers over the last 25 years. According to Google Scholar he has an h-index of 32 and an i10-index of 85.

Keynote Title: Artificial Intelligence in Education: where are we now?