Keynote Speakers
Keynote Speakers (Alphabetize by Last Name)
Prof. Lap-Pui Chau, IEEE Fellow
The Hong Kong Polytechnic University, Hong Kong, China
The Hong Kong Polytechnic University, Hong Kong, China
Short Bio: Lap-Pui Chau received the Ph.D. degree from The Hong Kong Polytechnic University 1997. He was with School of Electrical and Electronic Engineering, Nanyang Technological University from 1997 to 2022. He is currently a Professor in the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University. His research interests include machine learning, computer vision, and image & video analytics. He is an IEEE Fellow. He was the chair of Technical Committee on Circuits & Systems for Communications of IEEE Circuits and Systems Society from 2010 to 2012. He was general chairs and program chairs for some international conferences. Besides, he served as associate editors for several IEEE journals and Distinguished Lecturer for IEEE BTS.
Asst. Prof. Chao Huang
University of Hong Kong, Hong Kong, China
University of Hong Kong, Hong Kong, China
Short Bio: Chao Huang is an Assistant Professor at the Department of Computer Science at the University of Hong Kong (HKU). His research focuses on developing novel machine learning frameworks to tackle various challenges in Data Mining, Information Retrieval, Spatial-Temporal Data Analytics, User Behavior Modeling, Recommendation, Graph Mining, and Deep Representation Learning. Prior to that, he received his Ph.D. in Computer Science from the University of Notre Dame in USA.
Prof. Hisao Ishibuchi, IEEE Fellow, Chair Professor
Southern University of Science and Technology, China
Speech Title: Introduction to Evolutionary Multi-Objective Optimization: Basic Ideas and Challenges
Southern University of Science and Technology, China
Speech Title: Introduction to Evolutionary Multi-Objective Optimization: Basic Ideas and Challenges
Short Bio: Hisao Ishibuchi received his BS and MS degrees from Kyoto University, and his PhD degree from Osaka Prefecture University. Since 2017, he has been a Chair Professor at Southern University of Science and Technology, China. He was the IEEE Computational Intelligence Society (CIS) Vice-President for Technical Activities in 2010-2013, and the Editor-in-Chief of IEEE Computational Intelligence Magazine in 2014-2019. Currently, he is an IEEE CIS Administrative Committee Member, and an Associate Editor of IEEE Transactions on Evolutionary Computation, Evolutionary Computation Journal, and ACM Computing Surveys. He is/was General Chair of EMO 2027, IEEE WCCI 2024 and EMO 2021, and Program Chair of FUZZ-IEEE 2026, IEEE SSCI 2023, and IEEE CEC 2010. He is also Workshops Chair of IEEE CAI 2026, Area Chair of NeurIPS 2025, and Senior Program Committee Member of AAAI 2026. He received a Fuzzy Systems Pioneer Award from IEEE CIS in 2019, an Outstanding Paper Award from IEEE Transactions on Evolutionary Computation in 2020, and Best Paper Awards from FUZZ-IEEE 2009, 2011, EMO 2019, 2025, and GECCO 2004, 2017, 2018, 2020, 2021, 2024. He also received a JSPS prize in 2007. He is an IEEE Fellow.
Abstract: Real-world optimization problems usually have multiple conflicting objectives. Such a multi-objective problem has no single optimal solution which optimizes all objectives. It has a large number of Pareto optimal solutions with different tradeoffs among objectives. In the last three decades, various evolutionary multi-objective optimization (EMO) algorithms have been proposed to search for a set of well-distributed solutions on the entire Pareto front. In this talk, first I will explain some basic concepts in multi-objective optimizations such as dominance relation, non-dominated solutions, Pareto optimal solutions, and Pareto front. Next, I will explain basic ideas of well-known frequently-used EMO algorithms such as NSGA-II, MOEA/D, NSGA-III and SMS-EMOA. I will also explain some weaknesses of those algorithms. Finally, I will briefly explain some important new research directions in the EMO field.
Prof. Jiawei Jia, Chair Professor, IEEE Fellow
Dean of Institute of Artificial Intelligence and Future Networks
Director of Interdisciplinary Intelligent Supercomputing Center
Beijing Normal University, (BNU-Zhuhai), China
Dean of Institute of Artificial Intelligence and Future Networks
Director of Interdisciplinary Intelligent Supercomputing Center
Beijing Normal University, (BNU-Zhuhai), China
Short Bio: Prof. Weijia Jia is currently a Vice President and Chair Professor at Beijing Normal University (BNU)-Hong Kong Baptist University (HKBU) United International College (UIC), and a Professor at BNU in Zhuhai, China. He also serves as the Director of the Joint BNU-UIC Institute of Artificial Intelligence and Future Networking. Previously, he held positions as Chair Professor and Deputy Director of the State Key Laboratory of Internet of Things for Smart City at the University of Macau and Zhiyuan Chair Professor at Shanghai Jiaotong University.
Prof. Jia holds a BSc and MSc from Central South University, China, and a PhD in Computer Science from the Polytechnic Faculty of Mons, Belgium. He has published over 500 papers in prestigious journals and conferences, with a current H-index of 67 and more than 15,000 citations. His research focuses on AI theory and algorithms, including NLP, optimal network routing, intelligent edge computing, and sensor networking. He has received numerous awards, including the 1st Prize of Scientific Research from China's Ministry of Education in 2017 and multiple provincial science and technology awards.
Prof. Jia is a Fellow of IEEE, a Distinguished Member of the China Computer Federation (CCF), and has been recognized among the Top 2% of life scientists on the Stanford List (2020-2022).
Prof. Ping Li
The Hong Kong Polytechnic University, Hong Kong, China
The Hong Kong Polytechnic University, Hong Kong, China
Short Bio: Dr. Ping LI, National Distinguished Young Expert, is currently an Assistant Professor with the Department of Computing and an Assistant Professor with the School of Design, The Hong Kong Polytechnic University, Kowloon, Hong Kong. Prior to that, he was an Assistant Professor at the Macau University of Science and Technology, Taipa, Macau, and a Lecturer at The Education University of Hong Kong, Tai Po, Hong Kong.
Dr. Li received his Ph.D. degree in CSE from The Chinese University of Hong Kong, Shatin, Hong Kong.
He has published over 150 top-tier vision and graphics papers refereed, including IEEE TVCG, TIP, TNNLS, TMI, TMM, TCSVT, TCYB, TBME, TSMC, TII, CVPR, NeurIPS, AAAI, ACM SIGGRAPH VRCAI. He has an excellent Creative Media project reported worldwide by Science News Line, ScienceWeek, Science Bulletin, EurekAlert!, ACM TechNews, etc.
His current research interests are computer vision and creative media, including image/video stylization, colorization, artistic rendering and synthesis, computational art, interactive design, big data visualization, human-computer interaction, 2D/3D animation, GPU acceleration, virtual and augmented reality.
Assoc. Prof. Hai-Ning Liang
Hong Kong University of Science and Technology (Guangzhou), China
Speech Title: Enabling More Intelligent, User-tailored Interaction in Mixed Reality
Hong Kong University of Science and Technology (Guangzhou), China
Speech Title: Enabling More Intelligent, User-tailored Interaction in Mixed Reality
Short Bio: Hai-Ning Liang is an Associate Professor within the Computational Media and Arts Thrust at the Hong Kong University of Science and Technology (Guangzhou). He was previously a full Professor in the Department of Computing at Xi'an Jiaotong-Liverpool University (XJTLU), where he served as its founding Head (2019-2023) and the Deputy Director of the Suzhou Municipal Key Lab for Intelligent Virtual Engineering and the XJTLU Virtual Engineering Centre. He received his PhD in computer science from the University of Western Ontario in Canada. His research focuses on the design and evaluation of novel interactions and applications for virtual and mixed reality, gaming, and visualization technologies. He has published over 300 papers, some of which have won awards and recognitions, including the 2024 IEEE ICDM 10-year Highest-Impact Paper Award, Best Paper Award (Honorable Mention) at ACM ISS'24, and Best Paper (Honorary Mention) at IEEE VR'24. He serves on the editorial boards of several journals and is a member of the organization and technical committees of the leading conferences in his research area.
Abstract: Mixed reality (MR) systems have the potential to transform significantly how we interact with digital content and the physical world around us. Compared with traditional systems, interaction in MR is based on a more flexible and diverse set of input devices that allow users to interact with virtual objects and environments in more natural, intuitive, and varied ways. However, interaction in MR also tends to be imprecise, inefficient, and cumbersome. In this talk, I will briefly review the main interaction paradigms in MR, describe some of their challenges, and provide some solutions that can make interaction more intelligent and tailored to users' specific needs and the context/application scenario to help address issues with imprecise and inefficient operations. I will focus on discussing approaches that can model user behavior patterns, which can then help us develop interactions that are optimized for accuracy, efficiency, and usability across various scenarios.
Assoc. Prof. Chen Lyu
Nanyang Technological University, Singapore
Nanyang Technological University, Singapore
Short Bio: Chen Lyu is an Associate Professor at School of Mechanical and Aerospace Engineering, and the Cluster Director in Future Mobility Solutions, Nanyang Technological University, Singapore. He joined NTU and founded the Automated Driving and Human-Machine System (AutoMan) Research Lab since June 2018. His research focuses on intelligent vehicles, autonomous driving, and human-machine systems, where he has published 4 books, over 200 papers, and obtained 12 granted patents. He serves as Senior/Associate Editor for IEEE T-ITS, IEEE TVT, IEEE T-IV, etc. He received many awards and honors, selectively including Nanyang Research Award (Young Investigator), Singapore National Academy of Science Young Scientist Awards Finalist, SAE Ralph R. Teetor Educational Award, Champions of Waymo Open Dataset Challenges at CVPR (2021, 2024), Innovation Prize at CVPR nuPlan Planning Challenge (2023), Most Innovative Award of NeurIPS Driving SMARTS Competition (2022), ITSC 2023 Best Paper Runner-Up Award, IEEE CIS-RAM 2024 Best Paper Award, etc.
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Assoc. Prof. Kezhi Mao
Nanyang Technological University, Singapore
Nanyang Technological University, Singapore
Short Bio: Dr. Mao obtained his BEng, MEng and PhD from Jinan University, Northeastern University, and University of Sheffield, respectively. Since obtaining his PhD, he has been working at School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, where he is an Associate Professor. Dr. Mao's expertise spans several subfields of artificial intelligence (AI), including machine learning, computer vision (CV), natural language processing (NLP), and information fusion. In recent years, he has directed his research focus toward the dynamic and transformative domain of NLP such as large language models (LLM).
He has been ranked among the Stanford-Elsevier World's Top 2% Scientists in both career-long and single-year categories from 2020 to 2025. He is placed within the top 0.5% globally in the field of AI & Image Processing.
Prof. Hongliang Ren
The Chinese University of Hong Kong, Hong Kong, China
The Chinese University of Hong Kong, Hong Kong, China
Short Bio: Professor Hongliang Ren received his Ph.D. in Electronic Engineering (Specialized in Biomedical Engineering) from The Chinese University of Hong Kong (CUHK) in 2008. He has been navigating his academic journey through Chinese University of Hong Kong, UC Berkeley, Johns Hopkins University, Children's Hospital Boston, Harvard Medical School, Children's National Medical Center, United States, and National University of Singapore. He has served as an Associate Editor for IEEE Transactions on Automation Science & Engineering (T-ASE) and Medical & Biological Engineering & Computing (MBEC). He has served as an active organizer and contributor on the committees of numerous robotics conferences, including a variety of roles in the flagship IEEE Conf. on Robotics and Automation (ICRA), IEEE Conf. on Intelligent Robots and Systems (IROS), as well as other domain conferences such as MICCAI/ROBIO/BIOROB/ICIA/CVPR. He served as publicity chair for ICRA 2017, concurrently as Organizing Chair for ICRA 2017 workshop on Surgical Robots, and video chair for ICRA 2021. He has delivered numerous invited keynotes/talks at flagship conferences/workshops at ICRA/IROS/ROBIO/MICCAI/CVPR/ICIA. He is the recipient of IFMBE/IAMBE Early Career Award 2018, Interstellar Early Career Investigator Award 2018, Health Longevity Catalyst Award (2022 by NAM & RGC), NUS Engineering Young Researcher Award (2019), Interstellar Early Career Investigator Award (2018), ICBHI (Biomedical and Health Informatics) Young Investigator Award (2019), NUS Young Investigator Award (2013), EMedic Global Gold Medal (2017) and Silver Medal (2021), Best Paper Awards in IEEE-ROBIO (2019 & 2013), IEEE-RCAR2016, IEEE-CCECE2015, IEEE-Cyber2014 among 30+ others awards.
Prof. Benjamin W. Wah, IEEE Life Fellow, ACM Fellow, AAAS Fellow
Research Professor of Computer Science and Engineering, Provost Emeritus, CUHK
Chinese University of Hong Kong, Hong Kong, China
Research Professor of Computer Science and Engineering, Provost Emeritus, CUHK
Chinese University of Hong Kong, Hong Kong, China
Short Bio: Benjamin Wah (Fellow, IEEE) received the PhD degree from UC Berkeley. He is currently a research professor and was previously the provost of the Chinese University of Hong Kong. He is also professor emeritus with the University of Illinois, Urbana-Champaign. His research interests include nonlinear optimization and multimedia signal processing. He cofounded the IEEE Transactions on Knowledge and Data Engineering in 1988 and served as its editor-in-chief between 1993-1996. He received the IEEE-CS Technical Achievement Award in 1998, the IEEE Millennium Medal in 2000, the Raymond T. Yeh Lifetime Achievement Award from the Society for Design and Process Science in 2003, the IEEE Computer Society W. Wallace-McDowell Award in 2006, and the IEEE-CS Richard E. Merwin Award and IEEE-CS Technical Committee on Distributed Processing Outstanding Achievement Award both in 2007. He has served the IEEE Computer Society in various capacities, including vice president for Publications (1998 and 1999) and president (2001). He is a fellow of the ACM and the AAAS.
Prof. Shengdong Zhao
City University of Hong Kong, Hong Kong, China
Speech Title: Heads-Up Computing: Towards the Next Interaction Paradigm for
Wearable Intelligent Assistants
City University of Hong Kong, Hong Kong, China
Speech Title: Heads-Up Computing: Towards the Next Interaction Paradigm for Wearable Intelligent Assistants
Short Bio: Shengdong Zhao is a Professor in the School of Creative Media and
the Department of Computer Science at City University of Hong Kong. He
established and led the Synteraction (formerly NUS-HCI) research lab
in 2009 at the National University of Singapore. Prof. Zhao received
his Ph.D. in Computer Science from the University of Toronto and a
Master's degree in Information Management Systems from the University
of California, Berkeley.
With extensive experience in developing innovative interface tools and
applications, Prof. Zhao is a regular contributor to top-tier HCI
conferences and journals like CHI, ToCHI, Ubicomp/IMWUT, CSCW, UIST,
and IUI. He served as a senior consultant with Huawei Consumer
Business Group in 2017. An active member of the HCI community, Prof.
Zhao serves on program committees for major HCI conferences and was
the paper co-chair for ACM SIGCHI conference in 2019 and 2020, and is
the paper co-chair for ACM UIST conference in 2025.
Prof. Zhao introduced the concept of Heads-up Computing in 2017,
contributing to several key projects and publications in this area,
including a featured article on heads-up computing in the September
2023 issue of Communications of the ACM. His research aims to develop
innovative interface tools that enhance daily life through this new
interaction paradigm. For more information about his work, please
visit www.shengdongzhao.com.
Abstract: Heads-up computing, an emerging paradigm in human-computer
interaction (HCI), aims to create seamless interactions with
technology through wearable intelligent assistants. This vision relies
on three crucial components: (1) bodily compatible hardware, (2)
multimodal complementary interactions, and (3) interfaces that
accommodate fragmented attention and are aware of potential resources.
Recent advancements in large language models (LLMs) have significantly
accelerated progress in these areas, enabling more natural,
context-aware, and proactive systems. These developments are pushing
heads-up computing beyond simple notifications to complex, multi-modal
interactions that blend seamlessly with our environment and daily
activities, allowing for efficient information processing in everyday
life. However, as we integrate these AI-driven assistants more deeply
into our lives, we must carefully consider ethical implications such
as privacy and cognitive load. Balancing technological advancement
with human-centered principles is crucial to create systems that
enhance productivity while respecting user autonomy and well-being,
ultimately augmenting human capabilities without compromising
fundamental values.
Prof. Hong Zhang, Chair Professor, IEEE Fellow
Fellow, Canadian Academy of Engineering
Southern University of Science and Technology (SUSTech), China
Fellow, Canadian Academy of Engineering
Southern University of Science and Technology (SUSTech), China
Short Bio: Dr. ZHANG Hong is currently a Chair Professor in the Department of Electronic and Electrical Engineering at Southern University of Science and Technology (SUSTech) where he directs "Shenzhen Key Laboratory on Robotics and Computer Vision". His research interests include robotics, autonomous vehicles, computer vision, and image processing. Prior to joining SUSTech, he was a Professor in the Department of Computing Science, University of Alberta, Canada, where he worked for over 30 years. He held an NSERC Industrial Research Chair from 2003-2017, and made significant contributions in robotics research. He served as the Editor-in-Chief of IROS Conference Paper Review Board, a flagship conference of the IEEE Robotics and Automation Society (RAS), from 2020-2022. He is currently serving a three-year term as a member of the Administrative Committee (AdCom) of IEEE RAS (2023-2025). In recognition of his many contributions, Dr. Zhang was elected a Fellow of IEEE and a Fellow of the Canadian Academy of Engineering.
Keynote Speakers in Past CEII
Prof. ChingYee Suen, IEEE FellowConcordia University
The Chinese University of Hong Kong
City University of Hong Kong
Prof. Ron Sun, IEEE FellowRensselaer Polytechnic Institute, USA
The University of Tokyo
Shenzhen Institue of Advanced Technology
Prof. Minghua Cheng, IEEE FellowCity University of Hong Kong
Hong Kong University of Science and Technology, China
University of Missouri, USA
Prof. Kun Yang, IEEE FellowUniversity of Essex, UK
Hong Kong Shue Yan University, China
University of Leicester, UK