جست‌وجوی استاد و پژوهشگر

Yan Liankeمشاهده پروفایل

استاد

• Chinese Literature
• Creative Writing
• Literary Theory
• +۸ مورد دیگر

Prof. Yan Lianke (born 1958) is a renowned contemporary Chinese writer and academic. He currently holds the IAS Sin Wai Kin Professor of Chinese Culture at Hong Kong University of Science and Technology and serves as Professor at the School of Liberal Arts of Renmin University of China. His work spans novels, short stories, and literary theory, often exploring political, historical, and social themes through a critical lens. Education: BA in Political Education (Henan University, 1985), MA in Literature (PLA Academy of Art, 1991) Awards: Lu Xun Literature Prizes, Franz Kafka Prize, Newman Prize, and international recognition for his humanistic and socially conscious writing Yan’s research and writing focus on the intersection of literature, memory, and truth-telling in authoritarian contexts. His theoretical work, such as the 2020 lecture On Memory , critiques the erasure of personal and collective recollection in modern China. His novels, including Four Books and Dreams of Ding Village , are celebrated for their allegorical depth and spiritual realism. Scientific awards and honors include: 2014 Franz Kafka Prize (first Chinese recipient) 2017 Dream of the Red Chamber Award 2021 Newman Prize for Chinese Literature 2022 Lee Hochul Prize for Peace 2024 Nebula Award for Contribution to Global Chinese Literature Yan’s teaching and creative writing programs at HKUST and Renmin University emphasize the ethical role of literature in documenting human experiences and challenging historical amnesia. His work has been translated into over 30 languages, with more than 150 foreign publications.

Brian Kwokمشاهده پروفایل

دانشیار

• Communication Design
• Visual Culture
• Information Design
• +۴ مورد دیگر

Brian Kwok is an Associate Professor at The Hong Kong Polytechnic University's School of Design, where he serves as Programme Leader of BA Communication Design and heads the Information Design Lab. His academic foundation includes an MA in Design from PolyU, complemented by an MA in Visual Culture Studies and MPhil in Communication from the Chinese University of Hong Kong. With over a decade of tenure at PolyU, Kwok co-founded the Information Design Lab in 2011 to advance research in practical design applications. Kwok's research explores the intersection of visual communication, cultural heritage, and urban environments. Primary domains include: Neon Signage Studies : Documentation and semiotic analysis of Hong Kong's vanishing neon landscapes Healthcare Communication : Typographic legibility for medication labeling targeting senior citizens Urban Ethnography : Spatial practices of street vendors and visual narratives in public spaces Cultural Preservation : Archival projects on Hong Kong's typographic heritage and vernacular design His publication corpus (2015-2023) demonstrates consistent focus on Hong Kong's visual culture evolution, with recurring themes: cultural identity in urban signage, typographic accessibility for vulnerable populations, and cinematic representations of urban change. Methodologically, he blends empirical studies (e.g., user testing of medicine labels) with visual semiotics and historical documentation. Awards recognize both scholarly and practical impact: GRF-funded research on neon sign preservation (2023) Arts Go Digital grant for cultural documentation (2021) HKDA Global Design Excellence Award (2017) Outstanding Paper Award for neon signage research (2017) As Lab Leader, Kwok oversees projects including medicine label optimization, wayfinding systems, and the Fading of HK Neon Visual Culture Project. He actively engages with public institutions through roles on the Public Libraries Advisory Committee and as external examiner for academic programs.

• Big Data Management
• Data Mining
• Graph Learning
• +۹ مورد دیگر

Dr. YANG, Renchi is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University, Faculty of Science. He earned his BEng in Software Engineering from Beijing University of Posts and Telecommunications and his PhD in Computer Science from Nanyang Technological University, followed by a postdoctoral fellowship at the National University of Singapore. His research is centered on developing efficient algorithms and systems for large-scale data management and analysis. His research interests include: Big Data Management and Analysis Graph Learning and Network Embedding Databases and Data Management (especially graph query processing and similarity search) The Web and Information Retrieval (search, ranking, recommendation, web mining) Data Mining and Machine Learning (social network analysis, text mining, large language models) Dr. Yang’s recent publications span top conferences such as KDD, SIGMOD, WWW, ICDE, and AAAI, focusing on scalable graph clustering, network embedding, GNNs, and LLM integration. His work emphasizes algorithmic efficiency, scalability, and practical applications in real-world graph data. Scientific honors include: VLDB 2021 Best Research Paper Award 2022 ACM SIGMOD Research Highlight Award Best Paper Award Nominee in WWW 2022 Honorable mention as best PC member in WWW 2022 Dr. Yang actively mentors PhD and research students, currently supervising several RPg students including LIN Xiaoyang, LAI Yurui, and ZHENG Haoran. He has secured research funding enabling PhD scholarships and research assistant positions. He serves on the program committees of major conferences like VLDB, KDD, WWW, and SIGIR, and reviews for journals including TKDE and VLDBJ. He is a key member of the Database Research Group at HKBU, which has published extensively in top venues, including 8 papers at SIGMOD 2023. His research lab, the LAGAS Group, focuses on large-scale graph analytics and systems. The team is actively working on projects involving graph clustering, embedding, GNNs, and integration with large language models. Dr. Yang is currently recruiting PhD students for 2026 and research assistants for 2025, indicating active and expanding research operations.

Li Chenمشاهده پروفایل

استاد

• Conversational AI
• Explainable AI
• Recommender Systems
• +۷ مورد دیگر

Professor Li Chen is a full Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU), with an affiliate appointment at the Academy of Wellness and Human Development. She leads the Positive Intelligence Lab , focusing on intelligent technologies for human well-being. Her research spans conversational AI, explainable AI, recommender systems, and human-computer interaction. Education: PhD in Computer Science, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (Nominee for Best PhD Thesis Award) Master in Computer Software and Theory, Peking University, China Bachelor in Computer Science, Peking University, China Her research interests revolve around personalized conversational and explainable AI, with applications in entertainment, education, e-commerce, and mental well-being. She has published over 150 papers in top venues including ACM TOIS, IJHCS, CHI, SIGIR, AAAI, RecSys, and UMAP . Her work has been recognized with awards such as the RecSys Best Student Paper Award (2024), CHI Honourable Mention (2022), and multiple best paper awards at UMAP and UMUAI. The most recent publications reflect a strong trend toward fair, explainable, and user-centric recommender systems , with increasing integration of large language models , mental health applications , and conversational agents . Her research emphasizes user feedback, negative sampling techniques, and evaluation frameworks grounded in real user behavior. Scientific Awards & Recognition: President’s Award for Outstanding Performance in Teaching (Individual), HKBU (2024/25) President’s Award for Outstanding Performance in Research Supervision (2022/23) World’s Top 2% Most-Cited Scientists, Stanford University (2021–2024) ACM Senior Member (2015) RecSys’24 Best Student Paper Award CHI’22 Honourable Mention Award UMAP’20 Best Student Paper Award UMUAI 2018 Best Paper Award THE Awards Asia 2021 Excellence and Innovation in the Arts (Co-I) Professor Chen is actively involved in mentoring PhD and Master’s students such as Wanling Cai and Yuhan Zhao, who have co-authored award-winning papers. She has secured research funding through grants like the HKBU IRCMS Project. Her editorial leadership includes serving as Co-Editor-in-Chief of ACM Transactions on Recommender Systems (TORS) , Associate Editor for ACM TiiS , and Editorial Board Member for UMUAI . She has chaired major conferences including ACM RecSys’23 (General Co-Chair), RecSys’20 (Program Co-Chair), and UMAP’18 (Program Co-Chair). She leads the Positive Intelligence Lab , which conducts interdisciplinary research on AI for well-being. The lab has developed datasets like the Intent Annotation of Recommendation Dialogue (IARD) and focuses on user-centric AI design, mental health chatbots, and personalized recommendation interfaces.

Bruno C.d.S. Oliveiraمشاهده پروفایل

دانشیار

• Programming Languages
• Modularity
• Functional Programming
• +۱ مورد دیگر

Dr. Bruno C.d.S. Oliveira is an Associate Professor at the University of Hong Kong's School of Computing and Data Science (SCDS), Department of Computer Science. He holds a DPhil from the University of Oxford (2008). Prior to his current position since 2013, he served as Research Professor at Seoul National University (2009-2011) and Senior Research Fellow at the National University of Singapore (until 2013). His research interests focus on Programming Languages , Modularity , Functional Programming , and Object-Oriented Programming . His work emphasizes foundational aspects like type systems, language design, and extensibility mechanisms. Notable articles include studies on type class implementations, functional graph programming, and meta-theoretical frameworks for programming language constructs. His research has been published in top venues such as POPL, PLDI, ECOOP, and ICFP. No scientific awards are explicitly mentioned in the provided text. Advising records and grant details are not listed, though his academic homepage at http://www.cs.hku.hk/~bruno may contain additional information.

XU Jingjun Davidمشاهده پروفایل

استاد

• Human-computer interaction
• Artificial Intelligence
• Recommendation systems
• +۵ مورد دیگر

Professor David Xu is a distinguished faculty member in the Department of Information Systems at City University of Hong Kong, where he has served as Professor since 2023 after progressing from Associate Professor (2017-2023). Prior to joining CityU, he held academic positions at Wichita State University from 2011-2017, culminating in the Bomhoff Endowed Professor of Business title in 2017. His educational background includes a PhD in Management Information Systems from the University of British Columbia (2011), an MPhil in Information Systems from City University of Hong Kong, and a First-class honors BBA in Business Administration from Lingnan University. As Programme Leader for both BBA Information Management and Bachelor's Degree in Information Systems programs since 2018, he plays a significant administrative role in curriculum development. Professor Xu's research spans human-computer interaction, artificial intelligence applications, and technology adoption across diverse domains. With over 90 publications including 40+ journal papers in top-tier venues like MIS Quarterly and Information Systems Research, his work demonstrates exceptional scholarly impact. His Google Scholar metrics (3,300+ citations, h-index of 22) reflect substantial influence in the field. His recent publications reveal a strategic focus on AI ethics, information cocoon mitigation in social media, healthcare applications of AI, and digital transformation effects on business. The work spans theoretical contributions and practical implementations, with increasing emphasis on societal impacts of technology. AIS Early Career Award (2018) AIS Distinguished Member – Cum Laude (2020) Multiple teaching excellence awards (2021, 2024, 2025) ICIS and ISR Best Associate Editor Awards (2020-2021) Numerous paper award nominations across major conferences Professor Xu has secured significant research funding including NSFC, RGC GRF, and CityU Strategic Research Grants totaling millions in funding. His current projects address critical issues like AI beauty filters, depression treatment systems, and information cocoon mitigation. As Senior Editor for Information Systems Journal and Associate Editor for Information Systems Research, he shapes the field's scholarly discourse while supervising DBA and PhD students across multiple programs.

Qiuyu Luمشاهده پروفایل

استادیار

• Ecological HCI
• Computational Design
• Bio-inspired & Biomimetic Design
• +۳ مورد دیگر

Dr. Qiuyu (Luca) Lu is an Assistant Professor (Presidential Young Scholar) at the School of Design of The Hong Kong Polytechnic University and Director of the Interbeing Lab , which focuses on designing intelligence for mutualism between humans, nature, and machines. He holds a Ph.D. in Design and a B.Eng. in Mechanical Engineering from Tsinghua University. Ph.D. in Design, Tsinghua University B.Eng. in Mechanical Engineering, Tsinghua University His research bridges Ecological HCI, Computational Design , and Bio-inspired Engineering , creating sustainable interactive systems that leverage natural processes. Recent projects include: RoboMoRe (2025): LLM-driven robotic morphology optimization Degrade to Function (2024): Programmable eco-degradable interfaces Sustainflatable (2023): Ambient energy harvesting for morphing devices His work has been exhibited internationally at Ars Electronica and the Milan Triennale . Scientific recognition includes a Best Paper Honorable Mention at UIST 2023. Dr. Lu is actively recruiting PhD students and postdocs across disciplines, including design, computer science, mechanical engineering, and materials science, with research tracks in: Experimental Track: Interactive hardware prototyping Computational Track: AI-aided design tools Design Track: User experience frameworks

Can Liuمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Spatial Computing
• +۵ 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.

• Software Security
• Artificial Intelligence
• Adversarial Machine Learning
• +۷ 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.

Shenghua Gaoمشاهده پروفایل

دانشیار

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

Louis Jean Munschمشاهده پروفایل

مدرس

• French Language Teaching
• French as a Foreign Language
• Language Acquisition
• +۲ مورد دیگر

Mr. Louis Jean Munsch serves as Lecturer in French and Modern Languages Coordinator at The Chinese University of Hong Kong (CUHK), a position he has held since joining the institution in 2015. His responsibilities include curriculum development and coordination of modern language programs. Education Background Mr. Munsch earned his Master's degree in French as a Foreign Language and Licence of Modern Letters from the University of Haute-Alsace, Mulhouse, France. During undergraduate studies, he concurrently obtained a university certificate in Swiss Studies. Prior to this, he received a National Diploma of Art from Le Quai, Superior School of Art and Design of Mulhouse. Research and Teaching Focus His expertise centers on practical French language pedagogy with emphasis on foreign language acquisition methodologies. Drawing from interdisciplinary training in art and Swiss cultural studies, he develops culturally immersive teaching approaches. International teaching experience across Hungary, Beijing, and Hong Kong informs his cross-cultural communication strategies and curriculum design for diverse student populations. Professional Experience Before CUHK, Mr. Munsch taught French at the Franco-Hungarian Youth Foundation in Hungary after passing the French National Board Certification Examination for Secondary Education. He also instructed at Alliance Française institutions in Beijing and Hong Kong, establishing foundational language programs for non-native speakers.

• Security and Reliability of VR/AR Systems
• Internet of Things and Mobile Sensing
• Blockchain and Distributed Systems
• +۷ مورد دیگر

Dr. Henry Hong-Ning Dai is an Associate Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He previously held academic positions at Lingnan University and Macau University of Science and Technology, where he advanced from Assistant to Associate Professor. He holds a Ph.D. from the Chinese University of Hong Kong and a D.Eng. from Shanghai Jiao Tong University. Education: Ph.D. in Computer Science and Engineering, Chinese University of Hong Kong (2008) D.Eng. in Computer Technology Application, Shanghai Jiao Tong University (2012) M.Eng. in Computer Science and Engineering, South China University of Technology (2003) B.Eng. in Computer Science and Engineering, South China University of Technology (2000) Dr. Dai's research focuses on security and reliability of VR/AR systems , Internet of Things , blockchain and distributed systems , federated learning , and cyber-physical systems . His work integrates AI, networking, and software engineering to address real-world security and performance challenges in emerging technologies. He has published over 300 papers in top journals and conferences such as IEEE JSAC, TMC, ICSE, INFOCOM, and AAAI, accumulating more than 24,000 citations. The 15 most recent publications (2023–2025) highlight his leadership in VR/AR security (e.g., AcouListener, Meta VR study), blockchain scalability and fairness (e.g., Porygon, Auncel, Justitia), federated and robust learning (e.g., EBS-CFL, FedDP), and edge-AI and wireless security (e.g., HARBOR, Smart Shield). His recent work also explores AI-generated art evaluation and LLM-driven manufacturing systems , showcasing interdisciplinary innovation. Scientific Awards and Recognition: Holder of 1 U.S. patent and 1 Australia innovation patent Winner of more than 17 awards Senior Member of ACM, IEEE, and EAI Dr. Dai has been Principal or Co-Investigator on over 12 research projects totaling HK$16 million, funded by UGC, NSFC, FDCT, and HKBU. He serves as an Associate Editor for IEEE Communications Surveys & Tutorials , IEEE Transactions on Intelligent Transportation Systems , and several other IEEE journals. He has chaired program committees and served on the PC of top conferences including ICSE, KDD, and INFOCOM. He is actively recruiting Ph.D. students and RAs in security, blockchain, and AI. Laboratories and Research Teams: While not explicitly named, Dr. Dai leads a research group focused on secure and intelligent distributed systems, with active projects in blockchain, VR security, and edge AI. His team has developed open-source tools such as VR-SP Detector , PrettySmart , and RLF for smart contract analysis and security assessment.

Wong K.K.Y.مشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Prof. Kenneth K.Y. Wong is an Associate Professor and Division Associate Head (AI & Data Science Division) at the School of Computing and Data Science (CDS), The University of Hong Kong. He holds a BEng from The Chinese University of Hong Kong and MPhil/PhD from the University of Cambridge in Computer Vision. His career spans over 20 years in academia, including roles as Associate Head of the Department (2008-2012) and Programme Director of the BEng(CompSci) programme (2008-2015). Research Focus: Computer Vision, Machine Learning, Medical Imaging, Generative Models Key Roles: Director of Computer Vision Laboratory, Associate Editor of IJCV His research emphasizes camera calibration, 3D model reconstruction, generative AI, and medical image understanding. Over 160 peer-reviewed publications appear in top venues like CVPR, ECCV, and TPAMI. Active in professional service, he serves on program committees of major AI/conference events. Grants include projects in medical imaging (e.g., mitral valve analysis) and autonomous driving (DriveGPT4 series). His lab focuses on cutting-edge topics like video diffusion models, text-to-image synthesis, and 3D avatar generation.

• Chinese Language & Literature

Dr. HU Haiying serves as a Lecturer II at the Language Centre of Hong Kong Baptist University, a central academic unit providing multilingual instruction across the university's programs. Her role focuses on language education within Hong Kong's bilingual academic environment. Research Interests Her expertise centers on Chinese Language & Literature, encompassing classical/modern Chinese literary traditions, linguistic structures of Mandarin and Cantonese, and pedagogical methodologies for teaching Chinese as a second language. This work supports cultural preservation through language education in higher education contexts. Scientific Awards No scientific awards were documented in the provided information. Advising and Grants Details regarding graduate student supervision, research grants, or funded projects were not specified in the available materials. Labs and Teams As a member of the Language Centre, she contributes to university-wide language education initiatives, though specific research teams or laboratory affiliations were not referenced in the source text.

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.