Find Academic Supervisors

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +4 more

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).

Jyh-An LeeView profile

Professor

• Intellectual Property
• Artificial Intelligence and the Law
• Law & Digital Technology
• +1 more

Jyh-An Lee is a Professor and founding Executive Director of the Centre for Legal Innovation and Digital Society (CLINDS) at The Chinese University of Hong Kong (CUHK) Faculty of Law. He leads the New Ventures Legal Team (NVLT) and holds advisory roles at institutions like the European Center for E-Commerce & Internet Law and National University of Singapore. Education : JSD (Stanford), LLM (Harvard), MBA & LLB (National Taiwan University) Admissions : Practicing lawyer in Taiwan His research interests focus on Intellectual Property , AI and the Law , Law & Digital Technology , and Asian Law . He has contributed to landmark studies on NFTs, metaverse legal frameworks, cybersecurity, and IP litigation in Asia. The scientific awards he has received include: CUHK PhD IMPAC Award (2024-25) CUHK Vice-Chancellor’s Exemplary Teaching Award (2023, 2019) CUHK Outstanding Research Impact Award (2022-23) Numerous other university and faculty-level honors His work has been cited by major international courts and agencies. He is also a TRAIL Academic Fellow and active in policy advisory roles for Creative Commons and IP offices in Taiwan and Hong Kong.

Hayden Kwok Hay SOView profile

Associate Professor

• Reconfigurable Computing
• FPGA-Based Systems
• Computer Architecture
• +7 more

Prof. Hayden Kwok Hay SO is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Electrical and Electronic Engineering. He currently serves as Acting Director of the School of Innovation and previously co-directed the Computer Engineering Program. His research focuses on reconfigurable computing systems, FPGA-based architectures, and their applications in AIoT, medical imaging, and high-performance computing. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (1998–2007). Prof. So has been recognized with awards such as the IEEE-HKN Teaching Award (2021), Croucher Innovation Award (2013), and multiple teaching excellence awards. He leads the Computer Architecture & System Research Lab (CASR) and co-founded the Joint Lab on Future Cities (JLFC). His work spans FPGA overlay architectures, graph processing systems, and hardware-software co-design for efficient computing. Key research contributions include advancements in FPGA-based reconfigurable systems, sparse dataflow architectures, and medical imaging accelerators. He has secured grants for projects like 'Advanced machine vision guided aquatic surface vehicles' and 'Efficient and Productive Parallel Data Processing in Hybrid FPGA-CPU Clusters.' Prof. So has advised numerous students and researchers, contributing to over 150 peer-reviewed publications. His current projects explore AI hardware acceleration, neuromorphic computing, and FPGA-driven solutions for big data challenges.

Damien CharrierasView profile

Associate Professor

• Cultural Studies
• Media Theory
• Digital Arts
• +7 more

Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship

Michael C.L. CHAUView profile

Professor

• Business Analytics
• Artificial Intelligence
• Web Mining and Social Media
• +8 more

Professor Michael C.L. CHAU serves as Professor and Deputy Area Head of Innovation and Information Management at The University of Hong Kong's Faculty of Business and Economics. He also holds the position of Associate Director at the HKU HKJC Centre for Suicide Research and Prevention, and serves on the HKU Senate and Court. His academic journey includes a Ph.D. in Management Information Systems from the University of Arizona and a B.Sc. in Computer Science (Information Systems) from the University of Hong Kong. Dr. Chau's research spans business analytics, artificial intelligence, web mining, fintech, smart health, and security informatics. His work focuses on applying data/text/web mining techniques to business, education, and social domains. He leads the Artificial Intelligence Research Group at HKU Business School, which has secured significant funding from the Hong Kong Research Grants Council, Food and Health Bureau, and other agencies for projects including 'The Invisible Hand in Crowdfunding' and 'Factors Moderating the Predictive Power of Social Media Sentiment on Stock Returns'. His publication portfolio includes over 150 articles in premier journals like MIS Quarterly, JMIS, and IEEE Transactions, with recent work exploring large language models, hate speech detection, and disaster-related social media analysis. His research demonstrates strong interdisciplinary connections across computer science, information systems, and business applications. INFORMS ISS Design Science Award (2020) IEEE ITSS Leadership Award in Intelligence and Security Informatics (2020) AIS Sandra Slaughter Service Award (2016) HKU Outstanding Young Researcher Award (2014) Faculty Research Postgraduate Supervision Award (2020 & 2025) Cited over 9,400 times (h-index = 47) Dr. Chau actively mentors doctoral students and has supervised numerous PhD graduates who now hold academic positions at institutions including Fudan University, Xi'an Jiaotong-Liverpool University, and the University of Maryland. His research grants portfolio demonstrates sustained funding success across diverse areas including blockchain, mental health applications, and social media analytics. The Artificial Intelligence Research Group he leads maintains strong industry connections through projects with Hong Kong Red Cross and the Hospital Authority.

Luo PingView profile

Associate Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +3 more

Professor Ping Luo is an Associate Professor and Assistant Director (Outreach and Advancement) at the School of Computing and Data Science, University of Hong Kong. He also serves as Associate Director (Innovation and Outreach) of the Musketers Foundation Institute of Data Science. His research focuses on developing advanced machine learning algorithms, particularly in computer vision and deep learning, emphasizing reinforcement learning, meta-learning, and foundational algorithm understanding. Luo holds a PhD from the Chinese University of Hong Kong (2014), supervised by Prof. Xiaoou Tang and Prof. Xiaogang Wang. His notable achievements include over 70 peer-reviewed publications in top venues like TPAMI, IJCV, ICML, and CVPR, alongside competition wins such as the 2014 ImageNet ILSVRC Challenge and the 2017 YouTube-8M Video Classification Challenge. His work spans applications in autonomous driving, video segmentation, and facial recognition. Education: PhD in Information Engineering (2014), Chinese University of Hong Kong Awards: 2011 HK PhD Fellow Award, 2013 Microsoft Research Fellow Award Professional Roles: Former Research Director at SenseTime Research Recruiting Postdocs, PhDs, and RAs His research interests include algorithm development for autonomous systems, deep learning foundations, and practical AI applications in computer vision. He maintains an active presence in academic outreach and industry collaboration.

Lingpeng KongView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +3 more

Dr. Lingpeng Kong is an Assistant Professor in the Department of Computer Science at the University of Hong Kong (HKU), affiliated with the School of Computing and Data Science. He obtained his PhD from Carnegie Mellon University in 2017, co-advised by Noah Smith and Chris Dyer. Previously, he was a research scientist at Google DeepMind (2017–2020). His research focuses on natural language processing (NLP), machine learning, and deep learning, particularly in structured prediction and representation learning. He co-directs the HKU NLP Lab. Notable contributions include work on syntactic parsing, neural architecture design, and lifelong learning. He has received an Outstanding Paper Award at EACL 2017. Dr. Kong teaches courses such as Natural Language Processing (COMP3361/COMP7607) and Machine Learning (COMP3314), and has advised multiple research projects at HKU.

• Machine Learning
• Deep Learning
• Foundation Models
• +11 more

Bo Han is an Associate Professor in the Department of Computer Science at Hong Kong Baptist University's Faculty of Science, where he leads the Trustworthy Machine Learning and Reasoning (TMLR) Group. He also holds a visiting scientist position at the RIKEN Center for Advanced Intelligence Project (RIKEN AIP) in Japan. His research focuses on developing trustworthy and efficient machine learning systems, particularly under imperfect data conditions such as noisy labels, out-of-distribution data, and weak supervision. Bo Han's research interests span Machine Learning , Deep Learning , Foundation Models , Causal Representation Learning , Weakly and Self-supervised Learning , Robustness and Security in Machine Learning , Federated Learning , and AI for Science . His work aims to build intelligent systems that can reliably learn and reason from complex, imperfect real-world data. His recent publications reveal a strong trend toward trustworthy foundation models , robust reasoning with large language models , out-of-distribution detection , privacy-preserving learning , and causal robustness . His research integrates theoretical foundations with practical applications, often published in top-tier venues like NeurIPS, ICML, ICLR, and TPAMI. Notable Awards and Honors: Outstanding Paper Award, NeurIPS Most Influential Paper, NeurIPS IEEE AI's 10 to Watch Award IJCAI Early Career Spotlight INNS Aharon Katzir Young Investigator Award Dean's Award for Outstanding Achievement RGC Early CAREER Scheme Bo Han has been actively involved in the academic community, serving as a Senior Area Chair and Area Chair for NeurIPS, ICML, and ICLR, and as an Associate Editor for IEEE TPAMI, MLJ, and JAIR. He has advised numerous PhD and research students and leads a globally distributed research group. His work is supported by major grants from RGC, NSFC, GDST, RIKEN, and industry partners including Microsoft, Alibaba, Tencent, and Baidu. He also leads research initiatives in Trustworthy Machine Learning , including projects on federated learning, model unlearning, privacy-preserving AI, and robust foundation models, often in collaboration with industry and international institutions.

Kening Ken ZhuView profile

Associate Professor

• Human-Computer Interaction
• Multimodal Interaction
• Tangible User Interfaces
• +9 more

Dr. Kening Zhu (Ken) is an Associate Professor jointly appointed by the School of Creative Media and the Department of Computer Science at City University of Hong Kong (CityU). His work focuses on innovative human-computer interaction techniques, with particular emphasis on creating novel interfaces that bridge digital and physical worlds. Dr. Zhu received his PhD degree from the National University of Singapore, where he was supervised by Professor Ryohei Nakatsu and Dr. Shengdong Zhao. He completed his Bachelor's degree in Computer Science at Huazhong University of Science and Technology in China. Dr. Zhu's research spans multiple areas within Human-Computer Interaction, with particular expertise in: Multimodal and Embodied Interaction (MEI) Mobile gesture interaction and tangible/wearable user interfaces Multimodal VR/AR systems Interactive digital fabrication and rapid prototyping Interaction design for children and educational technology His work often combines technical innovation with practical applications, focusing on making technology more accessible and intuitive for users across different contexts. Dr. Zhu has received numerous prestigious awards for his research contributions: Silver Medal at the 50th International Exhibition of Inventions Geneva (2025) Bronze Medal at the 48th International Exhibition of Inventions Geneva (2023) Bronze Medal at 2022 Inventions Geneva Evaluation Days First prize of Nokia Ubimedia MindTrek Awards (2011) He has also served as a jury member for the Nokia Ubimedia MindTrek Awards and as a reviewer for top-tier conferences and journals including SIGCHI, SIGGRAPH, and MobileHCI. As an active researcher and mentor, Dr. Zhu currently supervises multiple PhD students and research assistants. His research is supported by significant grants including ITF projects on Mixed Reality Assisted Preoperative Neurosurgical Planning and Development of Attention-Aware, Immersive, Collaborative Video Teleconferencing System. He also serves as Co-Principal Investigator for the TDG(CityU) START project focusing on interdisciplinary approaches in digital fabrication. Dr. Zhu established the MEI Lab (Multimodal and Embodied Interaction Laboratory) in 2017, which has become a hub for innovative HCI research at CityU. The lab focuses on creating next-generation interaction techniques that combine physical and digital elements, with applications ranging from healthcare to education and entertainment.

So, Man Cho, AnthonyView profile

Professor

• Optimization
• Algorithm Design
• Data Analytics
• +7 more

Anthony Man-Cho So is a Professor in the Department of Systems Engineering and Engineering Management at The Chinese University of Hong Kong (CUHK). He currently serves as Dean of the Graduate School and Deputy Master of Morningside College . With a BSE from Princeton University and a PhD in Computer Science from Stanford University, his career at CUHK began in 2007. Academic Leadership: Dean, Graduate School (2023–present); Deputy Master, Morningside College (2019–present) Education: BSE (Princeton), MSc/PhD (Stanford) His research focuses on optimization theory and its interdisciplinary applications in computational geometry, machine learning, signal processing, and statistics. Key projects include non-convex optimization for wireless networks, robust graph learning, and decentralized learning algorithms. His publications span high-impact journals like Mathematical Programming , SIAM Journal on Optimization , and conferences such as NeurIPS and ICML . Recent work emphasizes dynamic regret analysis , low-rank matrix recovery , and stochastic beamforming . He has authored over 50 refereed papers and a monograph on semidefinite programming. Awards include IEEE Fellow (2023), CUHK Research Excellence Award (2016–17), and multiple IEEE/INFORMS best paper and teaching accolades. He has served on editorial boards of journals like Mathematical Programming and SIAM Journal on Optimization , and as Lead Guest Editor for IEEE Signal Processing Magazine . Teaching roles include courses on optimization, discrete mathematics, and machine learning. Scientific Awards IEEE Fellow (2023) CUHK Outstanding Fellow (2019) Multiple IEEE/INFORMS Best Paper Awards (2010–2022) IEEE/UGC Teaching Awards (2008–2022) His methodology integrates theoretical rigor with practical applications, particularly in wireless communication systems, sensor networks, and financial engineering. Collaborations span institutions in Hong Kong, mainland China, and the U.S., reflecting a global academic influence.

Cheng, Reynold C.K.View profile

Professor

• Data Science
• Big Graph Analytics
• Uncertain Data Management
• +3 more

Professor Reynold Cheng is a faculty member at the University of Hong Kong (HKU), specifically within the Department of Computer Science in the School of Computing and Data Science (CDS). He currently serves as the Division Head of the AI & Data Science Division at CDS and is part of the Steering Committee of the Musketers Foundation Institute of Data Science. His academic journey includes a BEng and MPhil from HKU (1998–2000) and an MSc and PhD from Purdue University (2003–2005). Prior to HKU, he was an Assistant Professor at the Hong Kong Polytechnic University (HKPU) from 2005 to 2008. Cheng’s research focuses on data science, big graph analytics, and uncertain data management. He has received numerous awards, including the SIGMOD Research Highlights Reward 2020, HKICT Awards 2021, and HKU Knowledge Exchange Award (Engineering) 2021. His work has been recognized through grants such as the HKU-TCL Joint Research Centre for AI-funded project (HKD 1M, 2020–2022) and a CRF-funded project for real-time monitoring of infectious diseases (HKD 6.5M, 2021–2022). Cheng actively contributes to academic service, including serving as PC co-chair for IEEE ICDE 2021 and editorial roles in journals like IS and DAPD. His publications span top venues like SIGMOD, VLDB, and KDD, emphasizing algorithm design for large graphs and probabilistic data systems.

Liang YingyuView profile

Associate Professor

• Machine Learning
• Optimization in Deep Learning
• Generalization in Neural Networks
• +3 more

Dr. Yingyu Liang is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Computer Science and the Musketeers Foundation Institute of Data Science. Previously, he held an Associate Professor position at the University of Wisconsin-Madison and was a postdoc at Princeton University. He earned his PhD from Georgia Tech and holds M.S. and B.S. degrees from Tsinghua University. His research focuses on theoretical foundations of machine learning, particularly optimization and generalization in deep learning, robust machine learning, and practical applications. Key contributions include analyzing neural network feature learning, adversarial robustness, and contrastive learning efficiency. Education: PhD (Georgia Tech, 2014), M.S. (Tsinghua, 2010), B.S. (Tsinghua, 2008) Awards: NSF CAREER Award Labs/Groups: Research Group focused on theoretical ML and algorithm design Publications span top venues like NeurIPS, ICML, and ICLR, addressing topics such as deep learning theory, adversarial robustness, and graph representation learning.

Benjamin C.M. KaoView profile

Professor

• Database Management Systems
• Data Mining
• Real-time Systems
• +1 more

Professor Benjamin C.M. Kao is a faculty member in the Department of Computer Science at The University of Hong Kong (HKU), affiliated with the School of Computing and Data Science. He holds a BSc from HKU (1989) and a PhD from Princeton University (1995). His career includes roles as a teaching/research assistant at Princeton (1989-1991) and a research fellow at Stanford University (1992-1995). His research focuses on Database Management Systems, Data Mining, Real-time Systems, and Information Retrieval Systems. Notable contributions include S-OLAP for sequence data analysis, collaborative resource discovery in social tagging systems, and algorithms for mining periodic patterns in sequences. He has led research grants such as the GRF-funded 'Online Analytical Processing on Sequence Data' (2008) and computational studies in uncertain data mining (2006). Professor Kao has served on program committees for major computer science conferences and reviewed for leading journals. His work bridges theoretical foundations with practical applications in data systems and information retrieval.

Qihao WengView profile

Professor

• Remote Sensing
• GIScience
• Urban Climatology
• +5 more

Professor Qihao Weng is Chair Professor of Geomatics and Artificial Intelligence at The Hong Kong Polytechnic University, where he leads the Research Institute for Land and Space. A globally recognized scholar, he bridges geography, landscape ecology, and environmental science through innovative geospatial analytics, GeoAI, and big data methodologies. His work focuses on urban climatology, sustainability science, and human-environment interactions, with over 279 publications and 14 books. PhD, The University of Georgia MA, The University of Arizona MS, South China Normal University Professor Weng's research explores remote sensing applications for urban environmental challenges, including thermal comfort, heat islands, and land-use changes. He pioneered global-scale urban observation via the Group on Earth Observation (GEO) initiative and developed frameworks integrating geospatial technology with climate resilience strategies. Recent publications highlight advancements in GeoAI for urban thermal stress assessment, road extraction algorithms, and multi-temporal data fusion techniques. His work spans interdisciplinary domains, connecting remote sensing, urban science, and sustainability metrics across diverse climate zones. NASA Senior Fellowship (2008) Taylor & Francis Lifetime Achievements Award (2019) AAG Wilbanks Prize (2024) Lifetime Achievement in Remote Sensing Award (2024) Academia Europaea Foreign Member (2021) As Editor-in-Chief of the ISPRS Journal, Professor Weng has advanced global remote sensing discourse. His research has been supported by NSF, NASA, USAID, Microsoft, and Hong Kong Research Grant Council. He has delivered over 130 invited talks and established visiting professorships in Japan, France, and China.

Xihui LiuView profile

Assistant Professor

• Computer Vision
• Generative Models
• Multimodal AI
• +4 more

Xihui Liu is an Assistant Professor at the Department of Electrical and Electronic Engineering (EEE) and Institute of Data Science (IDS), The University of Hong Kong, with a courtesy appointment in the Department of Computer Science. She holds a PhD from the Chinese University of Hong Kong and a bachelor’s from Tsinghua University. Her research focuses on generative models, multimodal AI, computer vision, and their applications in embodied AI and AI for Science. Education: PhD in Multimedia Lab (MMLab), Chinese University of Hong Kong (2017–2021) Bachelor’s in Electronic Engineering, Tsinghua University (2013–2017) Research Interests: Generative models for 3D content and multimodal systems Embodied AI and vision-language integration Applications in scientific domains Awards: Adobe Research Fellowship (2020) Rising Stars in EECS (2021) WAIC Rising Stars Award (2022) Her work emphasizes interactive generative systems and benchmarks like T2I-CompBench. She co-organized workshops on multimodal foundation models and embodied AI, and currently serves as Area Chair for CVPR, NeurIPS, and ICLR.