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Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +۴ مورد دیگر

Kin Wai Michael Siu is the Eric C. Yim Professor in Inclusive Design and Chair Professor of Public Design at The Hong Kong Polytechnic University (PolyU) . He founded the Public Design Lab and directs two joint research centers: the PolyU-HIT Inclusive Environment Center and the PolyU-WUT Ship/Marine Aesthetic Design Lab . His roles include PhD/postdoc supervision, coordination of design research methods, and extensive editorial/advisory board memberships. PhD, The Hong Kong Polytechnic University PhD, University of Bath MSc, City University of Hong Kong MA, The Hong Kong Polytechnic University MEd, The University of Hong Kong BA(Hons), Loughborough University of Technology A leading figure in inclusive design, Siu integrates Vygotsky's ZPD and Bruner's scaffolding theory into his 'Scaffolding Innovation' framework. His work balances creative design with technological application, focusing on inclusive public spaces (playgrounds, country parks, recycling facilities) and pandemic prevention strategies (e.g., COVID-19/NID mitigation through design ). Recent projects explore AI-enhanced recycling , bioinspired wearables , and cultural heritage semiotics . His publications span design education , participatory design , and cross-cultural heritage preservation , with a fingerprint highlighting 'Public Design', 'Inclusive Design', 'Visually Impaired', 'Cultural Semantics', and 'Spatial Practice'. Key collaborators include researchers from Hong Kong, China, and international institutions. Scientific Awards : 2024 G Cross Award for Excellent Guidance (Instructor) 2024 Hong Kong Contemporary Design Awards for Exceptional Advisor Multiple international design/invention awards (over 100 total) 2008 Romanian Ministry Invention Awards for Rapid Demountable Platform (RDP) Awarded over 50 patents, Siu has secured numerous external grants for public design innovations. His Public Design Lab collaborates with institutions like Tsinghua University, MIT, and Cambridge, while his editorial roles span design, engineering, and education journals.

• Public Design
• Inclusive Design
• Participatory Design
• +۵ مورد دیگر

Stuart Hargreaves is an Associate Professor at the Faculty of Law , The Chinese University of Hong Kong . His research focuses on information and privacy law and constitutional law and legal theory , reflecting his prior legal practice and academic background. Education: SJD, University of Toronto (2013) BCL, Oxford University (2008) JD, Osgoode Hall Law School (2006) BA in Politics & Sociology, McGill University (2000) His work examines the intersection of artificial intelligence and legal education , with projects like “Teaching Avatars” using AI for educational content creation. He also investigates surveillance technologies , privacy law , and constitutional rights in the context of Hong Kong’s political and legal environment. Scientific Awards and Grants: CUHK Teaching Excellence Award (2017) CUHK Direct Grant for Research University Grants Committee Teaching Development Grant Research Grants Council General Research Fund Joseph-Armand Bombardier Canada Graduate Scholarship Google Policy Fellowship He has contributed to AI in legal pedagogy through multiple conference presentations (e.g., “Teaching Avatars” at the 2024 CUHK Teaching & Learning Innovation Expo) and serves on the Board of Advisors for Teach for Hong Kong . His external roles include journal reviewing and LAWASIA membership.

• Information Law
• Privacy Law
• Constitutional Law
• +۴ مورد دیگر

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

• Big Data
• Business Analytics
• Healthcare Analytics
• +۴ مورد دیگر

Dr. Wan Renjie is an Assistant Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He holds a BEng in Network Engineering from the University of Electronic Science and Technology of China and a PhD from Nanyang Technological University (NTU), Singapore. Prior to joining HKBU, he was a Wallenberg-NTU Presidential Postdoctoral Fellow (2020–2022) and a guest researcher at Peking University (2019–2020). His research focuses on computational photography, 3D vision, AI security, digital watermarking, and neural representations . He explores robustness and security in vision models, especially concerning NeRFs and 3D Gaussian Splatting, and develops methods for low-light enhancement, reflection removal, and domain adaptation. Dr. Wan has published in top-tier venues including TPAMI, IJCV, CVPR, ICCV, NeurIPS, AAAI, and ECCV . His recent work emphasizes copyright protection for neural 3D models , adversarial attacks in multimodal and event-based systems, and medical image reconstruction. He is actively mentoring PhD students and research assistants. VCIP 2020 Best Paper Award Outstanding Reviewer, ICCV 2019 He teaches courses such as Introduction to AI and ML (COMP3057) , AI Application Development (COMP3065) , and Python for Data Analysis and Machine Intelligence (COMP7035) . Dr. Wan leads a dynamic research group with ongoing projects on watermarking, 3D reconstruction, and AI security, and he is currently recruiting new PhD students and research assistants.

• Computational Photography
• 3D Vision
• AI Security
• +۱۲ مورد دیگر

Rynson W.H. Lau is a Professor of Computer Science at City University of Hong Kong (CityU), leading research in Computer Graphics, Computer Vision, and Deep Learning. He holds an Honorary Professorship at Swansea University. Previously, he served on faculties at Durham University and The Hong Kong Polytechnic University. His work focuses on advancing graphics and vision techniques, including deep learning applications for graphics/vision problems, with publications in top venues like SIGGRAPH, CVPR, and NeurIPS. He has received the Adobe Research Gift (2023) and the Springer Nature Editorial Contribution Award (2025) for his editorial contributions to the International Journal of Computer Vision . Education: B.Sc. (First-class Honors) in Computer Systems Engineering from University of Kent Ph.D. in Computer Science from University of Cambridge Research Interests: Computer Graphics: Focused on 3D reconstruction, rendering, and real-time performance capture. Computer Vision: Specializing in saliency detection, object recognition, and low-light scene enhancement. Deep Learning: Developing generative models and diffusion-based frameworks for graphics and vision tasks. Editorial Roles: Editorial Board Member, International Journal of Computer Vision and IET Computer Vision . Guest Editor for special issues in journals like ACM Transactions on Internet Technology and IEEE Transactions on Multimedia. Teaching: 2024/25 Academic Year: CS4185: Multimedia Technologies and Applications CS4188/CS5188: Virtual Reality Technologies and Applications Research Team: Advises over 20+ students and collaborates internationally. Recent projects include AI-driven VR systems for healthcare and advanced 3D content generation using diffusion models.

• Computer Graphics
• Computer Vision
• Deep Learning
• +۳ مورد دیگر

Prof. Yan Tina Luximon is a Full Professor and Associate Dean (Research) at the School of Design, The Hong Kong Polytechnic University. She chairs the School Research Committee, leads the Asian Ergonomics Design Lab, and serves as Deputy Discipline Leader for BA (Product Design). Her work bridges ergonomics, AI design tools, and 3D human modeling in cross-cultural contexts. Education: PhD in Ergonomics from The Hong Kong University of Science and Technology Research interests span Ergonomics in product design 3D digital human modeling for AI applications Anthropometry and cultural design differences Statistical modeling for head/face product development Human-computer interaction and AI visualization Recent publications focus on AI-enhanced 3D head modeling, ergonomic healthtech products, and cross-cultural design psychology, with applications in robotics, mobile technology, and medical devices. Scientific awards include: Gold Medal with jury congratulations at Geneva Inventions 2024 Silver Award at IDEA 2023 for adaptive eyewear design Best Innovation Award at ACED Japan 2017 She supervises postgraduate research and leads projects funded by the General Research Fund (RGC GRF) and Laboratory for AI in Design, including AI Powered Ergonomic Product Design (2025) and 4D Head Movement Prediction (2024).

• Ergonomic design
• Anthropometry
• 3D digital human modeling
• +۶ مورد دیگر

Zihao Fu is a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) . His work bridges computational methods with social sciences, focusing on model instability, repetition, hallucination, and algorithmic fairness. He has held research positions at the Oxford Internet Institute and the Language Technology Lab at the University of Cambridge. Education Ph.D. in Systems Engineering and Engineering Management (2017–2021), CUHK M.Eng. in Aeronautics and Astronautics (2012–2015), Beihang University B.Eng. in Automation Science (2008–2012), Beihang University His research explores the theoretical foundations of LLMs, addressing challenges like repetition , instability , and hallucination . He integrates linguistics , cognitive science , and fairness frameworks to enhance both foundational understanding and real-world applications of language technologies. Recent work includes biomedical NLP applications ( BAND dataset ), parameter-efficient model adaptation, and fairness toolkits ( OxonFair ). Zihao leads projects like BioCaster (disease outbreak monitoring) and CAM-Tool (cloud task distribution). He is actively mentoring postdoctoral researchers at CUHK and CUHK (Shenzhen), with expertise in machine learning , knowledge base integration , and parallel computing systems . His industry experience includes developing distributed algorithms at Alibaba Cloud’s PAI platform.

• Large Language Models
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Dr. Can Liu is an Assistant Professor at the School of Creative Media, City University of Hong Kong, where she leads the ERFI Lab (Laboratory of Empirical Research for Future Interfaces). Her research focuses on designing future interfaces for ubiquitous technologies through empirical understanding of human cognition and behavior, with emphasis on multimodal interaction combining physical and digital elements. Education: PhD in Human-Computer Interaction, Université Paris-Sud (France), INRIA labs ex)situ and ILDA MSc in Media Informatics, RWTH Aachen University (Germany) Dr. Liu's research spans three primary domains: AI-assisted Input (using LLMs/NLP to enhance text manipulation and speech interfaces), Spatial Computing (multimodal interfaces for AR/VR and large displays), and Hybrid/Remote Collaboration (supporting intuitive remote interaction through understanding collocated collaboration). Her work integrates empirical user studies with real-world system deployments in public spaces. Recent publications demonstrate strong trends toward LLM-integrated interfaces, wearable computing applications, and novel interaction techniques for foldable devices. Her team consistently publishes at top venues including CHI, UIST, and CSCW, with increasing focus on practical AI integration for everyday tasks. Awards and Recognition: Best Paper Award at ACM CHI 2014 (top 1%) Honourable Mention at ACM CHI 2012 (top 5%) Dr. Liu actively mentors PhD students and researchers while securing substantial research funding including Google Faculty Research Awards, National Natural Science Foundation grants, and RGC Early Career Schemes. She serves on numerous program committees including ACM CHI (Associate Chair 2024, 2022, 2021, 2020, 2019, 2017) and co-organizes research initiatives like the HCIX Summer Research Program. Her laboratory ecosystem includes the ERFI Lab, affiliation with the Augmented Materiality Lab and Kowloon Interaction Center, and active participation in the Greater Bay HCI community, supporting both fundamental research and industry collaboration with partners including Google, Huawei, and Lenovo.

• Human-Computer Interaction
• Artificial Intelligence
• Spatial Computing
• +۵ مورد دیگر

Professor Shenghua Gao is an Associate Professor at the School of Computing and Data Science of the University of Hong Kong (HKU), concurrently serving as Assistant Director for Shanghai Initiatives. He holds a PhD from Nanyang Technological University. His research focuses on integrating machine learning, spatio-temporal data analysis, and database systems to address challenges in mobility prediction, traffic management, and geospatial representation learning. He has contributed significantly to trajectory modeling, indexing frameworks for multi-dimensional data, and the application of large language models (LLMs) in spatio-temporal contexts. Key research interests include: Spatio-Temporal Data Science: Developing frameworks for efficient processing and analysis of point cloud, trajectory, and traffic data. Machine Learning for Databases: Innovating indexing algorithms (e.g., BMTree, MAST) and query optimization techniques leveraging ML. Trajectory and Mobility Prediction: Creating personalized models for next-location prediction and transfer learning across regions. Geographic AI (GeoAI): Enhancing road network representation and urban function inference using physics-guided and foundation models. Recent work highlights include the ST-LLM+ framework for traffic prediction, the MAST system for point cloud analytics, and the exploration of City Foundation Models for urban challenges. His publications span top venues in databases (SIGMOD, VLDB) and AI/data science (ICML, NeurIPS). While no awards are explicitly mentioned, his prolific output and leadership roles indicate significant academic contributions. He is actively involved in teaching and supervising research in the School’s undergraduate and postgraduate programs, including MSc(AI) and MPhil/PhD tracks.

• Spatio-temporal Data Analysis
• Machine Learning
• Database Systems
• +۴ مورد دیگر

Prof. Henry Ma is Professor and Programme Leader of the Doctor of Design programme at The Hong Kong Polytechnic University's School of Design, where he also leads the Creativity and Design Education Laboratory. He holds concurrent visiting professorships at Southwest Jiaotong University, Zhejiang University of Technology, and Beijing Film Academy. His academic credentials include a PhD from PolyU, MBA from University of Leicester, MA in Mass Communications from University of Leicester, and Adv. Dip from Hong Kong Academy for Performing Arts. Research Interests: Prof. Ma's work centers on creativity research, design education methodologies, and applications of design thinking. Key domains include: Creative process and innovation strategies Digital media design and animation pedagogy Studio-based flipped classroom approaches Tacit knowledge construction in design education Entrepreneurship frameworks for designers His publication trends (2021-2024) demonstrate strong focus on pedagogical innovation in design education, particularly exploring studio-based learning, tacit knowledge transfer, and technology-enhanced teaching methods. Recent works frequently examine flipped classrooms, OER integration, and motivational frameworks for creative professionals. Awards & Honors: Creative Industry Leader Award in China (2012) 1st Hong Kong Digital Entertainment Industry Person of the Year (2007) PolyU School Award in Services (2016) Projects & Leadership: Prof. Ma directs the Creativity and Design Education Lab and has secured significant grants including: HK$3.167M for Automatic Music Arrangement System (Innovation Fund) HK$3.1M for Game Content Creation Platform (Innovation Fund) HK$1M MOOC on Design Thinking (eLearning Fund) He serves as Vice-Chairman (Education) of Hong Kong Digital Entertainment Association and Honorary Advisor to ACM SIGGRAPH Hong Kong.

• Design Education
• Creativity Research
• Design Thinking
• +۴ مورد دیگر

Yang Yuxiang is an Assistant Professor at the University of Hong Kong's School of Computing and Data Science. His research focuses on software security, adversarial machine learning, and AI safety, with a particular emphasis on formal methods and large language models. He holds a PhD from Hong Kong. Research interests include: Automated program repair using LLMs Cybersecurity in open-source ecosystems Adversarial attacks on vision-language models Formal verification of theorem provers Ethical implications of AI systems Recent publications explore cutting-edge topics such as causality-aware safety testing for autonomous systems , smart contract vulnerability detection , and large model safety at scale . His work bridges theoretical foundations with practical applications in secure software development and AI ethics.

• Software Security
• Artificial Intelligence
• Adversarial Machine Learning
• +۷ مورد دیگر

Dr. LI Yuanxi, Kristen is a Lecturer in the Department of Computer Science at Hong Kong Baptist University. She holds a Ph.D. in Computer Science and an M.Sc. in IT Management from the same institution. Her research focuses on semantic multimedia indexing, adaptive search engines, link prediction using big data, infectious disease modeling, inclusive education, and web usability design. Education: Ph.D. in Computer Science, Hong Kong Baptist University M.Sc. in IT Management, Hong Kong Baptist University Her research explores innovative methods for multimedia retrieval and search engine design, with applications in social media analysis and public health. She actively engages in pedagogical research to enhance teaching methodologies. Recent Workshops: Organized the 2017 Joint Design Workshop on 'Design for Sustainability (D4S)', available on YouTube. Her publications emphasize semantic technologies and ontology-driven systems to improve information retrieval effectiveness.

• Semantic Multimedia Indexing and Retrieval
• Adaptive Search Engine Design
• Link Prediction Based on Multimedia Big Data
• +۳ مورد دیگر

Dr. Hailiang Wang is an Assistant Professor at the School of Design , The Hong Kong Polytechnic University. As a Presidential Young Scholar , he leads research at the intersection of human factors engineering , health informatics , and gerontechnology . PhD in Human Factors Engineering, The University of Hong Kong MSc in Industrial Engineering and Logistics Management, The University of Hong Kong BSc in Management, Dalian University of Technology His research integrates VR/AR , AIoT , and wearable sensor systems to develop intelligent healthcare solutions for aging populations. Key areas include: Fall risk assessment and prevention Medical UX/UI design Age-friendly technology Occupational safety systems Recent publications demonstrate expertise in systematic reviews , meta-analysis , and human performance modeling . His work contributes to UN Sustainable Development Goals for Health and Well-being and Quality Education. Scientific recognitions include: 3rd Runner Up, Co-Creating Learning Shorts Competition (2023) Outstanding Young Researcher, PolyU (2022) Best Paper Awards

• Human Factors and Ergonomics
• Human-Computer Interaction
• Health Informatics
• +۴ مورد دیگر

Chen Wang is an Assistant Professor in the Department of Statistics and Actuarial Science at The University of Hong Kong. He holds a PhD in Statistics from the National University of Singapore (NUS). His research focuses on Random Matrix Theory, Time Series Analysis, and High-dimensional Data Analysis. His work explores theoretical foundations and applications in econometrics, multivariate statistics, and high-dimensional inference. Key contributions include studies on spurious factor analysis, spectral distribution of time series, and cointegration analysis in large VARs. His teaching includes courses such as STAT2602 (Probability and Statistics II) and STAT3600 (Linear Statistical Analysis). Recent publications highlight advancements in AI-driven methodologies for single-cell biology, molecular modeling, and biomedical applications. Notable trends include integrating AI agents for experimental design, spatial biology analysis, and deep learning for medical imaging. Chen's work bridges statistical theory with practical applications, emphasizing high-dimensional data challenges in diverse scientific domains.

• Random Matrix Theory
• Time Series Analysis
• High-dimensional Data Analysis