| Cheng Siong LeeBIO: Assoc Professor Lee’s multi-disciplinary research spans IT, Digital Health, Signal/Image Processing, FinTech, Learning Analytics, Explainable AI, Deep ML, Computer Vision, Multi-agent Autonomous Systems for sustainable environment development. His 200+ papers published in SCImago Q1 journals: IEEE TSP, IEEE TKDE, IPM, Neurocomputing, Expert Systems with Applications, Automation-in-Construction, CACIE, Computer Methods & Program in biomedicine, etc; and in CORE A/A* Int-Conf proceedings: AAAI, IJCAI, ICDM, ICWS, ICDE, PAKDD, CIKM, ACM KDD, ACMMM, IEEE IC Signal Processing, etc. Lee has delivered keynote speakers for several IEEE/ACM Flagship conferences and General Chair/Co-chair of steering and technical program Committees. He has supervised completion 28 PhDs. |
Aslina BaharumTs. Dr Aslina Baharum is an Associate Professor and UX Researcher at the School of Engineering and Technology, Sunway University. Previously, she was a Senior Lecturer at Universiti Teknologi MARA (UiTM), and Universiti Malaysia Sabah (UMS). She also has industry experiences where she worked as an IT Officer for the Forest Research Institute of Malaysia (FRIM). She had experienced more than 20 years in the IT field. She received a PhD in Visual Informatics (UKM), a Master Science degree in IT (UiTM) and graduated Bachelor of Science (Hons.) in E-Commerce from UMS. She is a member of the Young Scientists Network - Academy of Science Malaysia, Senior Member IEEE, and certified Professional Technologist from MBOT, and served as MBOT/MQA auditor. She won several medals in research and innovation showcases and was awarded several publication awards, teaching awards, Excellence Service award, and UMS Researchers Awards. She has co-authored and editor books, published several books of chapters (>20), technical papers in conferences and peer-reviewed and indexed journals (>60) papers. She also served as editor for several journals, scholarly contributed as a committee, editorial team and reviewers, and given several invited/ plenary talks at conferences. Her research interests include UX/UI, HCI/Interaction Design, Product & Service Design, Software Engineering & Mobile Development, Information Visualization & Analytics, Multimedia, ICT, IS and Entre/Technopreneurship. Her workshops and talks covered Entrepreneurship, Video/Image Editing, E-Commerce/Digital Marketing, AR/VR/MR/XR in STEM, Design Thinking and etc. She is also a Certified Professional Entrepreneurial Educator, Executive Entrepreneurial Leaders and HRDF Professional Trainer. Title: Humanizing AI: Redefining User Experience in the Age of Intelligent Systems Abstract: As artificial intelligence (AI) becomes increasingly integrated into everyday life, designing user experiences that are both intuitive and adaptive has emerged as a critical challenge. The field of AI-User Experience (AI-UX) seeks to bridge the gap between human needs and intelligent technologies, ensuring AI systems enhance, rather than hinder, our digital interactions. However, current AI implementations often struggle with transparency, user control, and personalization, creating barriers to user trust and adoption. This keynote addresses these challenges by exploring the intersection of AI and UX design, aiming to redefine user experiences in the age of intelligent systems. The objective is to provide a framework for developing human-centered AI solutions that prioritize user engagement and ethical considerations. Utilizing a combination of design thinking approaches, user behavior analysis, and AI-driven interaction modeling, the study identifies key principles for creating adaptive interfaces and predictive systems that are both useful and usable. The findings reveal strategies for improving user satisfaction by incorporating explainability, personalization, and proactive feedback mechanisms into AI-driven interfaces. The hope is that this research will guide practitioners in designing AI-powered products that are not only functional but also empathetic, thus fostering a more seamless and human-centered integration of AI into digital ecosystems. |
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| Chuan Qin Chuan Qin received his Ph.D. degree in signal and information processing from Shanghai University, Shanghai, China, in 2008. Since Dec. 2008, he has been with the faculty of University of Shanghai for Science and Technology, where he is currently a Professor. He was with Feng Chia University at Taiwan as a Postdoctoral Researcher from July 2010 to July 2012. His research interests include multimedia intelligent computing, AI security, data hiding and image processing in encrypted domain. He has published over 200 peer-reviewed papers in journals and conferences, such as IEEE TIP, IEEE TIFS, IEEE TMM, IEEE TCSVT, and ACM MM. He has also published one book and held seven authorized patents. He was selected as the Highly Cited Chinese Researchers by Elsevier in 2020 and the World’s Top 2% Scientists in 2020-2024. He won the Excellent Paper Awards of CIHW 2016 and ChinaMFS 2023, and the Candidate of Excellent Paper Award of IEEE IIHMSP 2014. He has served as the Associate Editor for ACM TOMM, Neural Networks (Elsevier) and Information Fusion (Elsevier). Speech title：Image Copy Detection Based on Perceptual Hashing Abstract: Nowadays, Image copy detection is an important task on Internet and social media platform, which can be effectively used to achieve image copyright protection and authentication. In this talk, we will focus on how to realize image copy detection with perceptual hashing technique. First, the concept of perceptual hashing and its differences with cryptographic hash function and semantic retrieval hashing are given. Then, representative methods of perceptual image hashing for copy detection are introduced detailedly, including traditional methods and deep learning-based methods. Finally, the summary and further research directions are discussed. |
