Speaker: Prof. Albert Y. Zomaya, University of Sydney
Time: 20：00-21：00 Sept.24.2021
Host: Prof. Shu Yin
Abstract: In the past few decades, industrial automation has become a driving force in a wide range of industries. There is a broad agreement that the deployment of computing resources close to where data is created is more business-friendly, as it can address system latency, privacy, cost, and resiliency challenges that a pure cloud computing approach cannot address. This computing paradigm is now known as Edge Computing. Having said that, the full potential of this transformation for both of computing and data analytics is far from being realized. The industrial requirements are much more stringent than what a simple edge computing paradigm can deliver. This is particularly true when mission-critical industrial applications have strict requirements on real-time decision making, operational technology innovation, data privacy, and running environment. In this talk, I aim to provide a few answers by combining real-time computing strengths into modern data- and intelligence-rich computing ecosystems. I will also explore the topic of Edge AI, which is a process in which the Edge systems uses machine learning algorithms to process data generated by the user’s devices.
Bio: Albert Y. ZOMAYA is Chair Professor of High-Performance Computing & Networking in the School of Computer Science and Director of the Centre for Distributed and High-Performance Computing at the University of Sydney. To date, he has published > 600 scientific papers and articles and is (co-)author/editor of >30 books. A sought-after speaker, he has delivered >250 keynote addresses, invited seminars, and media briefings. His research interests span several areas in parallel and distributed computing and complex systems. He is currently the Editor in Chief of the ACM Computing Surveys and served in the past as Editor in Chief of the IEEE Transactions on Computers (2010-2014) and the Founding Editor in Chief IEEE Transactions on Sustainable Computing (2016-2020).