Keynotes
Prof Aad van Moorsel
Title: Models for Blockchain and Decentralised Systems
We consider blockchains and other decentralised systems from a performance and dependability engineering perspective. The presentation builds on several keynotes delivered in recent years by the author, which consider blockchain performance engineering in the system layer, the consensus layer and the incentives layer, respectively. In this keynote we provide an overall view on model-based performance and dependability analysis and on the software tools that support such modelling. We also discuss in some more detail the BlockSim simulation tool, recent model-based analysis results for the Verifier’s Dilemma and concerns for other emerging decentralised and distributed systems, including those for federated learning.
Bio:
Aad van Moorsel is a Chair in Decentralised Systems and Head of the School of Computer Science at University of Birmingham as well as Director of the institute of Interdisciplinary Data Science and AI in Birmingham and Turing Fellow of the Alan Turing Institute. His research group at University of Birmingham conducts research in security, privacy and trust, with applications in payment, trustworthy AI, blockchain and smart systems. The group’s research contains elements of quantification, be it through system measurement, predictive modelling or on-line adaptation. Aad worked in industry from 1996 until 2003, first as a researcher at Bell Labs/Lucent Technologies in Murray Hill and then as a research manager at Hewlett-Packard Labs in Palo Alto, both in the United States. He got his PhD in computer science from Universiteit Twente in The Netherlands and has a Masters in mathematics from Universiteit Leiden, also in The Netherlands. After finishing his PhD he was a postdoc at the University of Illinois at Urbana-Champaign, Illinois, USA, for two years. He is the author of over 200 peer-reviewed research papers and holds three US patents.
Yu Weng
Bio:
Yu Weng received the Ph.D. degree in computer science from the University of Science and Technology in Beijing, China, in 2010. He is currently a Professor of computer science at the Information Engineering Department, Minzu University of China. His current research interests include machine learning, cloud computing, and distributed computing.
Guosheng Yang
Bio:
Professor Yang Guosheng graduated from the Department of Automatic Control at Beijing Institute of Technology, where he obtained his Ph.D. in Control Theory and Control Engineering. After earning his doctorate, he joined the postdoctoral research station at the Institute of Automation, Chinese Academy of Sciences, focusing on multi-sensor fusion and image processing. He later went to Canada, serving as a visiting scholar at Concordia University and completing postdoctoral research at the University of Saskatchewan, where his research areas included image processing and emotion recognition. He is currently a professor at Hainan Digital Laboratory.
Wang Lei
Bio:
Wang Lei is a Research Fellow, Aerospace Information Innovation Institute, Chinese Academy of Sciences. The research direction is artificial intelligence technology for remote sensing data processing, with a focus on multi task remote sensing image interpretation and multi-modal remote sensing target tracking. He has published more than 20 academic papers in domestic and foreign academic journals, applied for more than 10 software copyrights, and 3 invention and utility model patents.
