Prof. Yiu-ming Cheung
Hong Kong Baptist University (HKBU), China
IEEE Fellow, AAAS Fellow, IET Fellow, AAIA Fellow, and British Computer Society (BCS) Fellow
Research Areas: Machine learning and visual computing, as well as their applications in data science, pattern recognition, multi-objective optimization, and information security.
Introduction: Yiu-ming Cheung is currently a Chair Professor (Artificial Intelligence) of the Department of Computer Science, Dean of Institute for Research and Continuing Education (IRACE), and Associate Director of Institute of Computational and Theoretical Studies in Hong Kong Baptist University (HKBU). He received PhD degree from Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2000, and then joined the Department of Computer Science at HKBU in 2001. He is an IEEE Fellow, AAAS Fellow, IAPR Fellow, IET Fellow, and British Computer Society (BCS) Fellow. He is the awardee of RGC Senior Research Fellow with receiving a fellowship grant of HK$7.8 million over a period of 60 months. Since 2019, he has been ranked the World’s Top 1% Most-cited Scientists in the field of Artificial Intelligence and Image Processing by Stanford University for six consecutive years. Furthermore, he has been elected as a Distinguished Lecturer of IEEE Computational Intelligence Society, and named a Chair Professor of Changjiang Scholars Program by the Ministry of Education of the People’s Republic of China for the dedication and exceptional achievements in his academic career. In addition, he is serving as the Editor-in-Chief of IEEE Transactions on Emerging Topics in Computational Intelligence. He was the Founding Chairman of IEEE (Hong Kong) Computational Intelligence Chapter and the Chair (2018-2022) of Technical Community on Intelligent Informatics (TCII) of IEEE Computer Society. He has served in various capacities (e.g., Organizing Committee Chair, Program Committee Chair, Program Committee Area Chair, and Financial Chair) at several top-tier international conferences, including IJCAI’2021, ICPR’2020, ICDM’2017 & 2018, WCCI’2016, WI-IAT’2012, ICDM’2006 & WI-IAT’2006, to name a few. He has been served as an Associate Editor for several prestigious journals, including IEEE Transactions on Cybernetics (2018-2023), IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Neural Networks and Learning Systems (2014-2020), ACM Transactions on Intelligent Systems and Technology, Pattern Recognition, Pattern Recognition Letters (2022-2024), Knowledge and Information Systems (KAIS), and Neurocomputing, as well as the Guest Editor in several international journals. Currently, he is an Engineering Panel member of Research Grants Council, Hong Kong, and a member of assessment panel of Enterprise Support Scheme (ESS) under the Innovation and Technology Fund (ITF). Also, he is a member of Fellow Evaluation Committee of IEEE Computer Society and IEEE Computational Intelligence Society, respectively.
Prof. Muhammad Khurram Khan
King Saud University, Kingdom of Saudi Arabia
Research Areas: Cybersecurity, Digital Authentication, Biometrics, Multimedia Security, Cloud Computing Security, and Technological Innovation Management
Introduction: Prof. Muhammad Khurram Khan is a global thought leader and influencer in cybersecurity. He is a Professor of Cybersecurity at the Center of Excellence in Information Assurance (CoEIA), King Saud University, Kingdom of Saudi Arabia. He is one of the founding members of CoEIA and has served as Manager R&D from March 2009 until March 2012. He, along with his team, developed and successfully managed the cybersecurity research program at CoEIA, which turned it into one of the best centers of excellence in the region. He is the founder and CEO of the "Global Foundation for Cyber Studies and Research", an independent and non-partisan cybersecurity think-tank in Washington, D.C., USA. He has contributed to cyber policy work for the G20 (Saudi and Italian Presidencies) in shaping a safer cyberspace for children, protecting the masses and vulnerable populations in cyberspace, and empowering and enabling women in the cybersecurity profession. In 2019, he played an instrumental role as a cybersecurity subject expert for a USD 6 million series B investment in a South Korean startup, "SecuLetter," which has received a corporate valuation of over USD 100 million (2023).
He is a fellow of the Institution of Engineering & Technology (UK), a fellow of the British Computer Society (UK), a fellow of the FTRA (Korea), a senior member of the IEEE (USA), a senior member of the IACSIT (Singapore), member of the IEEE Consumer Electronics Society, member of the IEEE Communications Society, member of the IEEE Computers Society, member of the IEEE Technical Committee on Security & Privacy, member of the IEEE IoT Community, member of the IEEE Smart Cities Community, and member of the IEEE Cybersecurity Community. He is also the Vice Chair of the IEEE Communications Society Saudi Chapter. He has been a distinguished lecturer of the IEEE (CTSoC) from 2019–2021. He is currently working as a chair of the task group (TG) of the International Telecommunication Union (ITU), a specialized agency of the United Nations on ICT, on child online protection in the Metaverse.
Prof. Teh Ying Wah
University Malaya, Malaysia
Research Areas: Data warehouse, data mining, deep learning, IoT, activity recognition, wearable sensors, accelerometers, heart arrhythmia, electrocardiograph, supraventricular premature beat, multivariate time series, edge computing, task scheduling, data streams, mobile computing, speaker verification, language recognition, clustering algorithms, MapReduce, stock market, and sentiment analysis
Introduction: With over 35 years of expertise in computer science and data mining, my research focuses on developing advanced data-driven solutions across multiple domains. I have made significant contributions in data mining, deep learning, IoT, and edge computing, with a strong emphasis on multivariate time series analysis, wearable sensors, and predictive analytics. My work in activity recognition, heart arrhythmia detection, electrocardiography, and speaker verification has advanced the use of machine learning in healthcare and biometric applications.
I have successfully secured and managed research grants exceeding RM one million, collaborating with public, private, and international organizations to drive impactful research. Notably, I have led two commercial data science projects with Petronas GTD and Air Liquide, applying advanced analytics to optimize industrial operations. My research also extends to MapReduce frameworks, stock market prediction, sentiment analysis, and mobile computing, enhancing real-time decision-making through big data techniques.
With over 90 publications in top-tier journals, I have contributed to the academic community through innovative research in clustering algorithms, task scheduling, and data streams. My work continues to bridge academia and industry, fostering new advancements in data science and intelligent computing solutions.