Prof. Shuang-Hua Yang, FIET, FInstMC, SMIEEE, is currently serving as the Vice Dean for Academic Affairs of Graduate School and a chair professor in the Department of Computer Science and engineering at SUSTech (Southern University of Science and Technology). Before joined SUSTech Professor Yang spent over 23 years in the UK Higher Education. He was the Head of Department of Computer Science at Loughborough University from 2014 to 2016. He joined Loughborough University in 1997 as a research assistant, and progressing to a research fellow in 1999, a lecturer in 2000, a senior lecturer in 2003, a professor in 2006, and Head of Department of Computer Science in 2014. He was awarded a Doctor of Science degree, a higher doctorate degree, in 2014 from Loughborough University to recognize his scientific achievement in his academic career. He is also an appointed expert at the national level in China. His research interests are mainly focused on Internet of Things and Cyber-Physical Systems. He authored four research monographs and over 200 academic papers.
Speech Title: Bayesian Network based Cyber-Physical Systems Risk Assessment
Abstract: Cyber-Physical Systems (CPS) refers to a new generation of intelligent systems with integrated computational performance and physical capabilities. However, with the expansion of CPS complexity and the enhancement of the system openness, most of CPS become not only safety-critical but also security-critical since deeply involving both physical objects, computer networks and communications. In the last decade, it is no longer rare to see safety incidents and security attacks happening in industries. This talk presents the identification of risks in CPS and a risk assessment model of CPS based on hierarchical Bayesian network topology. The feasibility of this model is veriﬁed by constructing an undesired event scenario on a sample CPS. The quantitative risk values are explained through qualitative risk analysis and assessment.
Prof. Dr Lili Yang is working in Southern University of Science and Technology in Shenzhen, China. She is also a reader in the School of Business and Economics at Loughborough University, UK. She has conducted a significant amount of research both independently and working in team. As the principal investigator she has led 14 projects and carried out 6 projects as co-investigator. The total budget has reached to over £5 million. Her recent publications appear in the top journals such as Applied Energy, Information Systems Research, European Journal of Operational Research, Technological Forecasting and Social Changes, to be named. She was invited by the UK Cabinet Office and gave a presentation to their staff in London. Her research has generated impact to the research community in the whole world.
Speech Title: Machine Learning based IoT Big Data Mining
Abstract: Internet of Things (IoT) is a system where the Internet is connected to the physical world via ubiquitous sensors. The technologies on which IoT is based are data collection, data transmission and data analysis. This talk introduces how machine learning can be applied for big data analysis generated by IoT in the applications such as smart home, smart prison, smart industry and smart city. The talk is concluded as IoT devices capturing every aspect of human life, environment, and industry and generate huge amounts of data. Machine learning techniques provide an efficient way to make use of such data for different purposes.