جست‌وجوی استاد و پژوهشگر

Yangjian QUANمشاهده پروفایل

استادیار

• Clean Energy
• Coordination Chemistry
• Inorganic Chemistry
• +۲ مورد دیگر

Yangjian QUAN is an Assistant Professor at the Department of Chemistry , The Hong Kong University of Science and Technology . His research focuses on Clean Energy , Coordination Chemistry , Inorganic Chemistry , and Organometallic Chemistry . Education: PhD in Chemistry from The Chinese University of Hong Kong (2015) Research Interests: He investigates catalytic methodologies using Metal-Organic Frameworks (MOFs) and organoboron compounds , emphasizing site-selective hydroboration , boron-centered radicals , and synergistic catalytic systems . His work bridges homogeneous and heterogeneous catalysis for sustainable chemical transformations. Key Trends in Publications: Recent studies (2023–2025) highlight boron–carbon diradicals , synergistic MOF catalysis , and photoinduced electron donor-acceptor complexes for borylation. Earlier work (2011–2018) established foundational methods in carborane cage B-H activation , electrochemical catalysis , and aggregation-induced emission of carborane materials. Advising and Grants: He supervises Doctor of Philosophy students (7 current) and one Master of Philosophy graduate (2023). Leading NSFC/RGC projects on machine learning-assisted confined catalysis (2025–), RGC Early Career grants (2023–), and Guangdong Province grants for sulfur-enriched MOFs in lithium-sulfur batteries (2024–). His teaching includes Advanced Inorganic Chemistry I (CHEM5310) and Capstone Research (CHEM4691/4692) courses.

LI Yuanxi, Kristenمشاهده پروفایل

مدرس

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

Pong C Yuenمشاهده پروفایل

استاد

• Video Surveillance
• Human Face Recognition
• Biometric Security and Privacy
• +۳ مورد دیگر

Pong C Yuen is a Professor in the Department of Computer Science and Associate Dean of Science Faculty at Hong Kong Baptist University (HKBU). He earned his B.Sc. (1989) from City Polytechnic of Hong Kong and Ph.D. (1993) from The University of Hong Kong. His academic career at HKBU spans since 1993, including a six-year term as Department Head (2011–2017). Dr. Yuen's research focuses on video surveillance , human face recognition , and biometric security and privacy . His work bridges theoretical advancements in deep learning , sparse representation , and domain adaptation with practical applications in medical imaging and human-computer interaction . Recent publications included in this summary demonstrate expertise in unsupervised learning for person re-identification, adversarial domain adaptation for anti-spoofing, and physiological signal analysis for biometric security. These works span venues like IEEE Transactions on Image Processing (TIP) , CVPR , and AAAI . Scientific awards include: University Fellowship (1996) Outstanding Editorial Board Service Award (2018) Guangdong Province First-prize Natural Science Award Ministry of Education China Second-prize Natural Science Award Fellow of IAPR As an educator, Dr. Yuen has taught courses ranging from fundamental programming to graduate-level medical image processing , with a focus on interdisciplinary applications. He has served as Editorial Board Member for journals like Pattern Recognition and SPIE Journal of Electronic Imaging , and as Vice President (Technical Activities) of the IEEE Biometrics Council.

Chen Wangمشاهده پروفایل

استادیار

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

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.

Shiqi Wangمشاهده پروفایل

دانشیار

• Semantic and Visual Communication
• AI Generated Content Management
• Information Forensics and Security
• +۳ مورد دیگر

Shiqi Wang is an Associate Professor in the Department of Computer Science at City University of Hong Kong. He holds a Ph.D. from Peking University (2014) and a B.Sc. from Harbin Institute of Technology (2008). His career includes postdoctoral and research roles at the University of Waterloo, Nanyang Technological University, and Microsoft Research Asia. He specializes in semantic/visual communication, AI content management, and image/video quality assessment. Education: Ph.D. in Computer Application Technology (2014), Peking University B.Sc. in Computer Science and Technology (2008), Harbin Institute of Technology Research focuses on Large Visual-Language Models (LVLMs) , Generative Face Video Coding , and Information Forensics . Recent work includes video coding innovations, AI-driven quality assessment, and bias mitigation in facial analysis. Awards include the IEEE Multimedia Rising Star Award (2021) , NSFC Excellent Young Scientist Fund (2020) , and multiple best paper awards at IEEE conferences. He serves as Associate Editor for IEEE Transactions on Image Processing and leads MPEG standardization efforts for generative video coding. Professional activities include TPC roles at ICML, CVPR, and ACM Multimedia. His lab actively collaborates on standards for generative AI and multimedia systems, with a focus on ethical AI and cross-domain applications.

Liu Qiمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• FinTech
• +۳ مورد دیگر

Qi Liu is an Assistant Professor at the Department of Computer Science, University of Hong Kong, and serves as Programme Director for the BASc(FinTech) Programme. He holds an MS from the National University of Singapore and a PhD from the University of Oxford. His research focuses on Natural Language Processing (NLP), Machine Learning (ML), and FinTech. He has contributed to leading conferences/journals such as NeurIPS, ICML, ICLR, ACL, and EMNLP, and actively serves on their program committees. His work includes advancements in relational memory models, causal inference, graph neural networks, and domain-specific representation learning. Key research areas include NLP applications in dialogue systems, counterfactual data augmentation for translation, and hyperbolic representations for knowledge graphs. Recent articles explore cutting-edge topics in photonics, spintronics, and memory device security, reflecting interdisciplinary interests. Education: MS (NUS), PhD (Oxford) Programme Role: BASc(FinTech) Director Email: liuqi@cs.hku.hk Homepage: leuchine.github.io No scientific awards are explicitly listed in the provided text. His research spans theoretical ML advancements and applied FinTech systems, with a focus on scalable NLP solutions and secure memory technologies.

Ken M. L. Yiuمشاهده پروفایل

استاد

• Databases
• Query Processing
• Spatiotemporal Data
• +۷ مورد دیگر

Ken M. L. Yiu is a Professor in the Department of Computing at Hong Kong Polytechnic University , Faculty of Engineering. He received his PhD and Bachelor's degree from the University of Hong Kong in 2006 and 2002, respectively, and was previously affiliated with Aalborg University (2006–2009). He is a leading researcher in databases, with a focus on spatiotemporal data, query processing, and multidimensional data management. PhD, University of Hong Kong (2006) Bachelor of Computer Engineering, University of Hong Kong (2002) His research interests lie at the intersection of database systems and spatial analytics. He investigates efficient indexing, query optimization, and privacy-preserving techniques for large-scale spatial and temporal datasets. His recent work explores learned index structures, GPU-accelerated query processing, and high-dimensional data retrieval. He has made significant contributions to spatial query processing, trajectory analytics, and location-based services. The trends in his recent publications (2021–2025) reflect a strong focus on high-performance database systems, including GPU acceleration (GHive), perfect hashing on GPUs (GPH), and learned cardinality estimation. His work increasingly integrates machine learning with traditional database techniques, as seen in AlayaDB for LLM inference and learning-based query optimization. He also continues to advance core database problems such as spatial indexing, trajectory analysis, and similarity search. SSTD 2025 10-Year Impact Award Ken Yiu has successfully led multiple competitive research projects funded by the Hong Kong GRF, including grants on learned index structures (2024–2026), smart memory for vector data mining (2021–2023), and efficient spatial data management (2017–2019). He has supervised numerous PhD and MPhil students, many of whom now hold academic positions (e.g., Bo Tang at SUSTech, Yu Li at HDU) or work in top tech companies (e.g., Huawei, Alibaba). His professional service is extensive, including roles as PI for major grants, area chair (ICDE 2024), and program committee member for top conferences like SIGMOD, VLDB, and ICDE. He is actively involved in research groups and projects related to database systems, particularly in spatiotemporal data management and efficient query processing. His lab collaborates closely with students and co-supervisors like Bo Tang on topics such as trajectory mining, spatial indexing, and learned databases. The research group maintains strong ties with international institutions and contributes to major open problems in database performance and scalability.

Francis C.M. Lauمشاهده پروفایل

استاد

• Parallel and Distributed Computing
• Wireless Networks
• Operating Systems
• +۶ مورد دیگر

Professor Francis C.M. Lau is a Professor at the University of Hong Kong's School of Computing and Data Science, within the Department of Computer Science. He holds an honorary professorship and has contributed extensively to academia through editorial roles and international society involvement, including pioneering the IEEE Computer Society's Distinguished Visitors Program for Asia/Pacific in 1993. His educational background includes a BSc from Acadia University and MMath/PhD from the University of Waterloo. Professor Lau's research focuses on parallel/distributed computing, wireless networks, operating systems, and computer music, with notable publications in journals like Theoretical Computer Science and Ad Hoc Networks . He has led major research grants, including a $7.5M HKU UGC Special Equipment Grant for interdisciplinary systems research. His awards include the IEEE Golden Core Recognition (1998) and the IEEE Third Millennium Medal (2000). He has served on key committees such as the Research Grant Council's engineering panel and Hong Kong Institution of Engineers' accreditation committee. His work bridges theoretical computer science with practical applications in networking, cloud computing, and cultural heritage through computational approaches to art.

Hailiang Wangمشاهده پروفایل

استادیار

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

Matthias Buehlmaierمشاهده پروفایل

دانشیار

• Quantamental Investing
• Text Analytics in Finance
• Natural Language Processing in Finance
• +۱۱ مورد دیگر

Matthias Buehlmaier is an Associate Professor of Teaching in Finance and Principal Lecturer at HKU Business School, University of Hong Kong, where he also serves as the BBA (IBGM) Programme Director. He holds a Ph.D. in Finance from Vienna Graduate School of Finance (WU Vienna), an M.S. in Mathematics from Texas A&M University, and a Vordiplom in Applied Mathematics from Ulm University, Germany. His research interests span quantamental investing, text analytics and natural language processing in finance, machine learning applications in financial markets, asset pricing, and market efficiency. He has pioneered the first university course worldwide on text analytics and NLP in finance, developed in 2018 and taught annually since then. His work bridges traditional finance with cutting-edge data science techniques, particularly focusing on how textual information affects financial markets and investment decisions. Buehlmaier has published in top finance journals including the Review of Financial Studies and Review of Finance, with research featured in the Harvard Law School Forum on Corporate Governance. His work on text analytics in finance has been particularly influential, demonstrating how textual analysis of financial media can inform investment strategies and market understanding. He has received numerous teaching and research awards including HKU's Outstanding Teaching Award, multiple Faculty Outstanding Teaching Awards, the Teaching Innovation Award, and the Hong Kong Asian Capital Markets Research Prize from HKSFA. His industry engagement includes connections with practitioners, regulators, and policy makers, with a focus on knowledge exchange and practical application of academic research. Buehlmaier has held visiting positions as a Fellow at University of Cambridge (Hughes Hall and Cambridge Judge Business School) through the Doris Zimmern HKU-Cambridge Hughes Hall Fellowship, and as a Visiting Scholar at Regensburg University's Department of Finance. Since April 2020, he has been an Advance HE Fellow, reflecting his commitment to excellence in higher education.

Maurice K.S. Tseمشاهده پروفایل

دانشیار

• Financial Markets
• Risk Management
• Asset Pricing
• +۶ مورد دیگر

Maurice K.S. Tse serves as Finance Associate Professor of Teaching at The University of Hong Kong's Faculty of Business, Department of Finance. With a distinguished career spanning several decades, Professor Tse has established himself as a leading expert in financial markets, risk management, and emerging financial technologies. His academic journey began with a Ph.D. in Finance from Michigan State University, where he demonstrated exceptional teaching abilities even as a candidate by winning the All-University-Excellence in Teaching Award in 1988. Professor Tse's educational background includes obtaining the professional qualification of Associate of the Society of Actuaries (ASA) in 1991. His academic path took him from the School of Business at Indiana University, which he joined in 1989, to Hong Kong University of Science and Technology (HKUST) where he taught professional courses for the Stock Exchange of Hong Kong in 1996, before settling at his current position at HKU. He has served on examination committees for the Society of Actuaries and as an external assessor for the University Grants Committee since 1995. Professor Tse's research interests span a wide spectrum of financial topics, with particular focus on government regulation effects on market volatility and wealth transfer, asset pricing, corporate finance, and risk management. His current research explores hybrid mortgage valuation, corporate acquisition signaling, Hong Kong market structure dynamics, and international currency-stock market responses to trade announcements. In recent years, his scholarly work has evolved to address contemporary financial technology challenges, including blockchain applications, cryptocurrency regulation, and AI's impact on financial markets and fraud prevention. His extensive publication record demonstrates a clear progression from traditional finance topics to cutting-edge financial technology research. Professor Tse has consistently produced high-impact work analyzing market structures, regulatory impacts, and emerging financial instruments. His recent articles reveal a strategic pivot toward digital finance, with significant contributions on stablecoins, blockchain security tokens, AI applications in finance, and cryptocurrency fraud prevention mechanisms, reflecting his ability to stay at the forefront of financial innovation. All-University-Excellence in Teaching Award (1988) Justice of the Peace (JP) appointment recognizing community service Professor Tse has maintained active engagement with professional financial institutions throughout his career. He has provided consulting services to the Stock Exchange of Hong Kong, prepared housing affordability reports for the Indiana Housing Finance Authority, and served on regulatory committees. His expertise is frequently sought for assessing market structures, regulatory impacts, and financial innovation. While specific grant information isn't detailed in the provided materials, his sustained research output across multiple decades suggests consistent funding support for his scholarly activities. Though specific laboratory affiliations aren't mentioned in the provided materials, Professor Tse appears deeply integrated into Hong Kong's financial research ecosystem, regularly contributing to policy discussions through publications in the Hong Kong Economic Journal and other venues. His work bridges academic research with practical financial market applications, particularly in the rapidly evolving areas of digital finance and regulatory technology.

WANG Donggenمشاهده پروفایل

استاد

• Activity-travel behavior
• Transport and time geography
• Activity-based socio-spatial segregation
• +۲ مورد دیگر

WANG Donggen is a Chair Professor in the Department of Geography at Hong Kong Baptist University (HKBU) and serves as Director of the Centre for China Urban and Regional Studies. His academic leadership spans editorial roles in major transportation journals and active participation in professional societies across Asia. Education: Ph.D. in Architecture, Eindhoven University of Technology, Netherlands M.A. in Development Studies, Erasmus University, Netherlands M.Sc. in Urban Design, Wuhan University, China B.Sc. in Geodesy and Geomatics, Wuhan University, China Research Focus: Professor Wang's work centers on activity-travel behavior and transport time geography , examining how built environments shape mobility patterns, socio-spatial segregation, and wellbeing. His research integrates machine learning for causal inference in travel behavior, with strong emphasis on Chinese urban contexts like Shenzhen and Beijing. Key themes include rail transit impacts, travel satisfaction determinants, and housing-residential satisfaction linkages. Publication Trends: Recent work (2022-2024) reveals growing interdisciplinary integration—combining transportation science with mental health studies, food accessibility research, and gendered mobility analysis. His methodological innovations in difference-in-differences frameworks and instrumental variable approaches address complex behavioral questions in urban settings. Scientific Recognition: Fellow, Hong Kong Society for Transportation Studies (2013–present) Grants & Service: Secured 5+ major grants from Hong Kong RGC (2022-2029) and NSFC, including AI-enabled geospatial platforms for disability mobility and rail transit behavior studies. As Co-Editor-in-Chief of Travel Behavior and Society and editorial board member for 5 top journals, he shapes global discourse in transportation geography. Previously chaired the Hong Kong Geographical Association (2009-2013). Research Infrastructure: Leads the Centre for China Urban and Regional Studies, driving collaborative research on urbanization, transportation systems, and regional development across Chinese cities through interdisciplinary teams.

Ravishankar Ramanathanمشاهده پروفایل

استادیار

• Quantum Cryptography
• Quantum Information Theory
• Device-Independent Quantum Information Processing
• +۳ مورد دیگر

Ravishankar Ramanathan is an Assistant Professor at the University of Hong Kong's School of Computing and Data Science, Department of Computer Science. His research spans Quantum Cryptography, Quantum Information Theory, and Human-Robot Interaction. He holds a PhD from the National University of Singapore (2013), with prior postdoctoral roles at The National Quantum Information Centre (Poland), Université Libre de Bruxelles, and the University of Oxford. His work includes foundational studies in quantum mechanics and advanced robotics applications, with over 30 refereed publications in top journals like Nature Communications and Physical Review Letters. Research interests focus on quantum device-independent protocols, randomness amplification, and human-centric robotics systems. His lab (QIFT Group: https://qift.weebly.com/) explores both theoretical quantum mechanics and practical robotics solutions for mobility assistance and social interaction. Recent publications highlight contributions to quantum cryptography (e.g., noise-tolerant protocols) and autonomous systems (e.g., robotic wheelchair navigation and social robot design). He collaborates internationally, bridging quantum theory with real-world robotics applications.

Edith Cheuk Han NGAIمشاهده پروفایل

دانشیار

• Internet-of-Things
• Edge Intelligence
• Data Analytics
• +۵ مورد دیگر

Dr. Edith Cheuk Han Ngai is an Associate Professor in the Department of Electrical and Electronic Engineering at the University of Hong Kong (HKU), where she has been since 2020. Previously, she held an Associate Professor position at Uppsala University, Sweden. Her research focuses on Internet-of-Things (IoT), edge intelligence, data analytics, machine learning, network security, smart cities, and health informatics. She is an ACM Senior Member, IEEE Senior Member, and IEEE ComSoc Distinguished Lecturer (2023-2024). Her research contributions include the Green IoT project in Sweden (2014–2017), recognized in IVA’s 100-list (2020). She has led interdisciplinary projects like the Smart Water Auditing initiative, combining IoT and machine learning to address water conservation. Ngai has received awards such as the VINNMER Fellowship (2009) and a Meta Policy Research Award (2022). Her work on energy-aware edge computing and federated learning has been widely cited, ranking her in the top 1% globally by Clarivate Analytics (2021–2023). Ngai serves as an Associate Editor for multiple prestigious journals, including IEEE Transactions on Mobile Computing and IEEE Transactions on Industrial Informatics. She has organized conferences like IEEE GreenCom 2022 and IEEE IWQoS 2024. Her lab, the HKU IoT Lab, explores AI-driven smart systems, edge general intelligence, and healthcare applications. Recent work includes Radio2Text (mmWave-based speech recognition) and HealthPrism (multimodal health analytics). Ngai advises a dynamic research group with postdocs and PhD students focused on federated learning, edge computing, and wearable health sensing. Notable students include Zhihan Jiang (HKU Foundation PhD Award 2024) and Sukanya Jewsakul (BuildSys 2024 Best Paper Candidate). She collaborates with institutions like the HKU Center for Water Technology and Policy on projects like smart water auditing and health informatics.

Taku Komuraمشاهده پروفایل

استاد

• Computer Graphics
• Physical Simulation
• Character Animation
• +۶ مورد دیگر

Roles & Affiliations: Professor of Computer Graphics at the Department of Computer Science, University of Hong Kong (since 2020). Previously at University of Edinburgh (2006-2020), City University of Hong Kong (2002-2020), and RIKEN (2000-2002). Holds a BSc, MSc, and DSc in Information Science from the University of Tokyo. Research Interests: Focuses on physically-based animation, character animation, 3D modeling, cloth animation, and robotics. Recent work emphasizes machine learning integration into animation synthesis. Notable projects include MotionNet (3D motion reconstruction), neural state machines for character interactions, and fracture simulation with material points. Publications: Over 100 peer-reviewed papers spanning SIGGRAPH, Eurographics, and IEEE journals. Recent work emphasizes deep learning applications in animation, medical imaging analysis, and physics-based simulations. Key trends include neural networks for motion synthesis, transformer-based models for 3D gestures, and topology-aware shape reconstruction. Awards: Royal Society Industry Fellowship (2014), Google AR/VR Research Award (2017). Recognized for contributions to physically-based animation and medical imaging AI. Labs & Collaborations: Leads research groups in computer graphics and AI at HKU. Collaborates with institutions on robotics, VR/AR, and medical imaging projects. Active in organizing SIGGRAPH and Eurographics conferences.