Keynote Speakers

Emerging artificial intelligence technologies in healthcare

Prof. Huiyu Zhou
School of Computing and Mathematical Sciences, University of Leicester, UK

Abstract of the talk:
Artificial intelligence has significantly influenced the health sector for years by delivering novel assistive technologies from robotic surgery to versatile biosensors that enable remote diagnosis and efficient treatment. While the COVID-19 pandemic is devastating, the uses of AI in the healthcare sector are dramatically increasing and it is a critical time to look at its impact in different aspects. In this talk, I will introduce the application of new deep learning models in medical image understanding. Then, I will discuss Parkinson’s disease (PD) whilst investigating the behaviour analysis of PD mice. I also present the use of machine learning technologies in sentiment analysis, followed by the discussion on several challenges.

Keywords: Artificial intelligence; healthcare; image segmentation; behaviour analysis; challenges.

Bio of the presenter:
Prof. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China, and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom. Dr. Zhou currently is a full Professor at School of Computing and Mathematical Sciences, University of Leicester, United Kingdom. He has published over 400 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “MIUA 2020 Best Paper Award”, “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". His research work has been or is being supported by UK EPSRC, ESRC, AHRC, MRC, EU, Royal Society, Leverhulme Trust, Puffin Trust, Alzheimer’s Research UK, Invest NI and industry. Homepage: https://www2.le.ac.uk/departments/informatics/people/huiyu-zhou.

Cybersecurity - A Game Theory Approach: Issues, modelling and computer science applications

Prof. Sardar M. N. Islam (Naz)  
Professor, ISILC, Victoria University, Melbourne, Australia. 
Distinguished Visiting Professor of Artificial Intelligence, UnSri. 

Abstract:
Cybersecurity is a multiagent system where intelligent agents interact, formulate strategies, fight, cooperate, coordinate, design systems, and plan actions to achieve their goals of cybersecurity or hacking and malicious damages. Game theory analyses and formulates strategies and designs rules or mechanisms for this cybersecurity multiagent system on the basis of artificial intelligence. For specifying, characterising and modelling and designing this intelligent multiagent system, mathematical game theory models of different forms can be developed, such as static, dynamic, evolutionary, differential and stochastic game theory models. Different algorithms such as Nash equilibrium, joint optimisation, evolutionary algorithms, neural networks, genetic algorithms, and other machine learning algorithms can be applied to different game theory models for analysing, solving, and computing these cybersecurity models. Findings from these models are used to formulate strategies, cooperate, coordinate, design systems, and plan actions by different intelligent agents and authorities in cybersecurity. Game theory application in cybersecurity is an important area in computer science for doing highly useful academic and practical cybersecurity activities and for academics and practitioners to build their careers. Therefore, it is necessary to prioritise this area of game theory in cybersecurity in computer science for research and development.

Short Bio:
Professor Dr. Sardar M. N. Islam (Naz) is Professior from Victoria University, Australia. As he has lived, studied, and worked in different countries and visited (extensively) different regions of the world for a long period, he adopts a global and humanistic approach in his research and academic works and he has undertaken rigorous scientific studies of emerging issues of different disciplines of artificial intelligence, business analytics, digitalisation, management science, etc. His academic work has gained international acclaim, resulting in many (1) Honours and Awards, (1) distinguished visiting or adjunct professorial appointments in different countries, (2) appointments in editorial roles of journals and (3) keynote speeches at international conferences in several countries. He has published 31 scholarly academic books in different disciplines. Each of these books makes significant scientific contributions to the literature. These books are published by prestigious publishers and the majority of books are published in highly regarded book series. He has also published about 250 articles, including some top leading international journal articles in his specialised research areas.

Improving Biometric Iris Recognition System Technology with Optimum Feature Extraction

Prof. A Taha
Auckland, New Zealand
Chengdu University, China

Abstract:
Iris-based biometric recognition systems have become an area of great research interest and been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. Consequently, researchers are focused on finding suitable features can extract from iris images that can be used as indexes the stored templates in a manner that enables access to and retrieval of those data by efficient search processes. We propose a method that extracts the most relevant features of iris images to facilitate minimization of the indexing time and the search area of the biometric database, the expected results will be showing a significant performance improvement in terms of bin miss rate and penetration rate compared with conventional methods.

Short Bio:
Dr A Taha is an Honorary Professor and External Advisor from New Zealand and High-end Foreign Expert at Widad University College & CDU. His research interests include improving biometric system technology with optimum feature extraction and various topics related to IT and medical research. His research results have been published in more than 50 papers in international journals and conferences, including various SCI/SCIE/IEEE indexing. He received various awards such as Chosen for Who’s Who in Medicine and Healthcare 2010. He is currently an editor board member for several international journals.

Corporate Knowledge Management Research: An Integrated Perspective

Lin Wang, PhD, Associate Dean, Distinguished Professor
Chinese Academy of Science and Education Research, Hangzhou Dianzi University, China

Abstract:
Knowledge management is the explicit and systematic management of vital knowledge - and its associated processes of creation, organization, diffusion, use, and exploitation. It is a process to help organizations identify, select, organize, disseminate, transfer knowledge. In this speech, I illustrate that how an understanding of knowledge and the knowing process differ from information and information management. Based on the taxonomy of explicit and tacit knowledge, I put forward a corporate knowledge management model. I also discuss the management strategies dealing with different kinds of knowledge. Nonaka's SECI model of knowledge creation and knowledge spiral process of knowledge theory are analyzed in detail. The innovation cycle and knowledge management cycle are compared. Three knowledge management models and traditions, documentalist, technologist, and learner & communicator models are introduced in the speech. I also discuss the success factors of corporate knowledge management. The difference in knowledge management in eastern and western countries is elaborated. Some main issues of knowledge management systems are briefly reviewed.

Biography:
Lin Wang is a distinguished professor of information science at Hangzhou Dianzi University. He was a visiting professor in University of California Berkeley, Nanyang Technological University. Lin is a guest research fellow in the National Information Resource Management Institute at Beijing. He was awarded Young Information Scientist by China Society for Scientific and Technical Information. He is a trustee of Tianjin Society for Chinese Information Research and Tianjin Association of Public Administration. He is also a member of editorial board of American Journal of Information Management. He has been elected as an expert of Xinhua News Agency Outlook Think Tank. He is a reviewer of program committee for many international conferences, such as iConference and ASIS&T. Recently Lin became the Session Chair (Long Paper) ACM/IEEE Joint Conference of Digital Libraries 2020. He got his PhD degree of information science from Peking University. His research interest includes foundation of information science and information philosophy. He has hosted more than 20 academic projects. He has published more than eighty academic papers in the international LIS journals like Journal of Documentation and Information Research, and leading peer-reviewed information science journals in China. His several papers were awarded as the best paper in the national academic organizations such as Chinese National S&T Information Society, Chinese S&T Communication Society.