جستجوی استاد راهنمای دانشگاهی

Cai Zhenguangمشاهده پروفایل

استاد

• Psycholinguistics
• Cognitive Psychology of Language
• Computational Linguistics
• +۳ مورد دیگر

Prof. Cai Zhenguang is a Professor in the Department of Linguistics and Modern Languages at The Chinese University of Hong Kong (CUHK), where he leads the Language Processing Lab affiliated with the Brain and Mind Institute. His research integrates behavioral, neuroscientific, and computational approaches to investigate language processing mechanisms. His educational background includes a PhD in Psychology from the University of Edinburgh. Prior to joining CUHK, he served as a lecturer at the University of East Anglia and held an ESRC Future Research Leader fellowship at University College London. Prof. Cai's research centers on psycholinguistics and cognitive neuroscience of language, with specific focus on language comprehension, production, and learning mechanisms. His lab investigates how interlocutors influence language processing, Chinese handwriting literacy including character amnesia, and whether large language models exhibit human-like language behaviors. Additional interests include psychophysics of magnitude perception where physical dimensions interact statistically. Recent publications (2024-2025) reveal strong trends in neural correlates of speaker-contextualized comprehension, computational modeling of language adaptation, and AI-human language comparisons - particularly in Chinese language phenomena. Key methodological approaches combine ERP/fNIRS neuroimaging with Bayesian modeling and deep learning techniques. Scientific recognition includes: ESRC Future Research Leader fellowship He has successfully advised multiple PhD students including Zebo Xu, Hanlin Wu, and Xufeng Duan, along with MA students like Tianyi and Yufeng Wu. His research is supported by significant grants: two General Research Fund projects as Principal Investigator (on character amnesia and interlocutor modeling), an Academic Equipment Grant for TMS-EEG systems, and a teaching grant for virtual behavioral research methodologies. The Language Processing Lab maintains active collaborations across disciplines, having organized major conferences including AMLaP Asia and CogSci Hong Kong Meetup, while recruiting researchers with expertise in fMRI, Bayesian modeling, and machine learning for ongoing projects.

Jiannong Caoمشاهده پروفایل

استاد

• Distributed Systems
• Blockchain
• Wireless Sensing and Networking
• +۴ مورد دیگر

Jiannong Cao is the Otto Poon Charitable Foundation Professor in Data Science and Chair Professor of Distributed and Mobile Computing at the Department of Computing, The Hong Kong Polytechnic University (PolyU). He currently serves as Dean of the Graduate School and directs multiple research entities including the Research Institute for Artificial Intelligence of Things (RIAIoT), Internet and Mobile Computing Lab (IMCL), and PolyU's University Research Facility in Big Data Analytics (UBDA). Previously, he was the Head of the Department of Computing from 2011 to 2017. Education : BSc from Nanjing University, MSc and PhD from Washington State University Prof. Cao's research focuses on distributed systems , blockchain , wireless sensing , big data analytics , machine learning , mobile cloud , and edge computing . His work includes over 800 publications, 34 patents, and leadership in 130+ research projects with HK$187 million in grants. Recent research trends highlight his contributions to blockchain interoperability , edge AI optimization , secure GPU execution , federated learning frameworks , and IoT-based control systems . These align with his expertise in distributed computing, blockchain, and data-driven intelligent systems. Scientific Awards : PolyU President Award for Excellent Performance/Achievement in Research Ministry of Education Higher Education Outstanding Scientific Research Output Awards – Natural Science (Second Class) China Computer Federation (CCF) Overseas Outstanding Contribution Award IEEE TCCLD Research Innovation Award Silver Medal at Geneva International Exhibition of Inventions Best Paper Awards across multiple IEEE conferences (2011-2021) Prof. Cao has secured over HK$187 million in grants from agencies like NSFC, MOST, RGC, ITC, and industry partners (Alibaba, IBM, Nokia). He has delivered 50+ keynote/invited talks and serves on editorial boards of top journals including IEEE TC, IEEE TPDS, and ACM ToSN. He leads research labs such as RIAIoT and IMCL, focusing on artificial intelligence of things, blockchain integration, and edge computing systems. Current projects include collaborative edge computing, Web3 policies, and secure autonomous cooperation in edge nodes.

Christian Wagnerمشاهده پروفایل

استاد

• Creativity Support
• Collective Intelligence
• Knowledge Management
• +۵ مورد دیگر

Professor Christian Wagner is a Chair Professor at the School of Creative Media, City University of Hong Kong, where he has served for nearly 30 years. He has held numerous significant administrative positions including Provost, Associate Provost (Quality Assurance), Chief Information Officer, and Associate Dean in both the School of Creative Media and College of Business. Wagner earned his PhD in Business Administration from the University of British Columbia in 1989, following earlier studies in Industrial Engineering where he obtained both a Diplom-Ingenieur (MSc equivalent) and Vordiplom (BSc equivalent). His academic career began at the University of Southern California before joining CityU. Professor Wagner specializes in creativity support systems, collective intelligence, knowledge management, and the use of computer games for learning. He is particularly renowned for his research on wikis and their impact on organizational performance. His work spans the intersection of information systems, virtual communities, and gamification, with fingerprint analysis showing strong connections to Wiki systems (100%), Information Systems (83%), Knowledge Management (58%), and Gamification (29%). His research contributes to multiple UN Sustainable Development Goals. Wagner's recent publications demonstrate a clear trajectory toward the intersection of artificial intelligence and cultural heritage, with significant work examining how large language models impact knowledge creation platforms like Wikipedia, while also exploring the role of generative AI in heritage practices and the dynamics of online communities through different developmental stages. Stanford's top 2% most highly cited scientists (2021-2024) Best Paper Award of HCI International 2018 Professor Wagner has supervised 21 documented research projects and numerous students, including PhD candidate Zijing SONG. His research is supported by multiple projects including "Amateur Esports and Health," "Synthetic Reality Immersion and Its Impact on Knowledge Transfer," and various gamification-related initiatives. With an h-index of 31 on Scopus and 4,666 citations, he maintains an active scholarly presence while continuing to explore the evolving relationship between technology, human collaboration, and knowledge creation. He has been actively involved in conference organization, serving as chair for multiple International Conferences on Human-Computer Interaction, demonstrating his leadership in the field of information systems and human-computer interaction.

• Computer Graphics
• 3D Computer Vision
• User Interaction
• +۵ مورد دیگر

Chi-Wing FU, Philip is a Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK). He holds dual roles in research and education, including Associate Editor-in-Chief of IEEE Computer Graphics and Applications. His research focuses on computer graphics, 3D vision, and human-computer interaction, with over 100 publications in top venues like SIGGRAPH, CVPR, and IEEE Visualization. Education: B.Sc. (1st Hons), Computer Science & Engineering, CUHK M.Phil., Computer Science & Engineering, CUHK PhD, Indiana University, Bloomington Research Interests: Dr. Fu's work spans 3D shape generation, computational LEGO design, AR visualization, and robotic interaction. He has pioneered projects like Make-A-Shape (large-scale 3D modeling) and DreamStone (text-driven 3D creation). His team also develops tools for medical data visualization and hand-object pose estimation. Recent Trends in Articles: Recent work emphasizes AI-driven creativity (e.g., LEGO art, text-to-3D systems) and real-time AR applications. His publications often bridge theory (e.g., generative models) with practical systems (e.g., user interfaces for design). Awards: Postgraduate Research Output Award (2023) MSRA Fellowship Nomination (2022) Best Associate Editor (IEEE CG&A) Outstanding Reviewer (ICCV 2021, CCF CAD/CG 2023) Advising & Grants: Supervised over 40 PhD/Master students and postdocs. Active in securing grants for projects like computational LEGO design (with Autodesk), medical AR visualization, and 3D generative AI. Collaborates with industry partners like Adobe and Huawei. Labs & Teams: Leads the Computational Design and Visualization Lab, focusing on 3D systems, robotics, and creative AI. Key projects include the LEGO Sketch Art toolchain and the HandShadowPoser AR system.

• High Energy Astrophysics
• Black Hole Accretion Disks
• Tidal Disruption Events
• +۷ مورد دیگر

Professor Lixin Dai is an Associate Professor in the Department of Physics at the University of Hong Kong, specializing in theoretical and computational high energy astrophysics. She received her BSc in Physics and Mathematics from HKUST (2005) and PhD in Physics from Stanford University (2012). Prior to her current role, she served as an Assistant Professor at the Niels Bohr Institute (University of Copenhagen) and holds the Sophie and Tycho Brahe Visiting Professorship there. Her research focuses on transient phenomena around astrophysical black holes, including tidal disruption events, accretion disks, jets, and gravitational wave counterparts. Education: B.Sc. HKUST (2005); M.Sc., Ph.D. Stanford University (2012) Her work spans multiple observational missions, co-chairing the Einstein Probe mission's Science Topic Panel and contributing to X-ray astronomy and relativistic simulations. She has secured significant grants from NSFC/RGC and HKU's General Research Fund, supporting studies on ultraluminous X-ray sources and super-Eddington accretion flows. Recent publications analyze magnetized accretion disks, wind dynamics, and gravitational lensing applications in tidal disruption events. Scientific awards include the Aspen Center of Physics Block Award (2018) and NSFC Excellent Young Scientist Fund (2021). She mentors PhD and MPhil students in astrophysics, teaches core courses like Astrophysics and Basic Research Methods, and participates in knowledge exchange activities such as public lectures on black holes and panel discussions at international festivals.

• Machine Learning
• Non-parametric Methods
• Computational Methods
• +۶ مورد دیگر

Yifan Chen is an Assistant Professor in the Department of Computer Science and affiliate faculty in the Department of Mathematics at Hong Kong Baptist University's Faculty of Science. He joined HKBU in Fall 2023 after completing his PhD in Statistics from the University of Illinois Urbana-Champaign in 2023 under the guidance of Prof. Yun Yang. His educational background includes: B.S. in Statistics from Fudan University (2018), advised by Prof. Juan Shen and Prof. Chenghong Zhang Ph.D. in Statistics from University of Illinois Urbana-Champaign (2023), advised by Prof. Yun Yang Dr. Chen's research focuses on developing efficient algorithms for machine learning, with particular emphasis on non-parametric models and neural networks featuring intensive matrix operations. His work bridges statistical theory with practical computational challenges in modern machine learning systems, especially those involving Transformers (language models) and Graph Neural Networks (GNNs). He approaches machine learning from both theoretical and applied perspectives, seeking to understand statistical structures while addressing real-world computational constraints. His publication record shows consistent output in top-tier venues including ICML, NeurIPS, KDD, and EMNLP, with recent work spanning graph coarsening, optimal transport, efficient language model fine-tuning, and causal inference. His research demonstrates strong mathematical foundations combined with practical applications in AI systems. Among his notable achievements: NSFC Young Scientists Fund (2025) GDSTC General Program funding (2024) RGC Early Career Scheme proposal grant (2024) ICML 2023 Grant Award ($1,500) Dr. Chen actively mentors students through his research group, supervising PhD students and visiting research assistants. He has successfully guided students who have gone on to PhD programs at institutions including Institute of Science Tokyo, HKU, Fudan, and NUS. His teaching includes COMP 7070 Advanced Topics in Artificial Intelligence and Machine Learning, which covers core machine learning concepts for AI application research, and COMP 2027 Applied Linear Algebra for Computing. His research group focuses on efficient machine learning algorithms, with current projects spanning graph neural networks, optimal transport, language model efficiency, and causal inference. He collaborates with researchers from institutions including UIUC, Fudan University, and industry labs like Amazon Alexa AI.

• Economic Theory
• Microeconomics
• Information Economics
• +۲ مورد دیگر

Thomas Brzustowski is an Assistant Professor in the Department of Economics at the University of Hong Kong, currently on leave from the University of Essex where he served as Assistant Professor from 2023 to 2025. His academic work centers on theoretical economics with applications to organizational design and market mechanisms. His educational qualifications are: PhD in Economics, London School of Economics, 2023 Brzustowski's primary research interests lie in economic theory and microeconomics, with specific focus on: Information Economics Mechanism Design Economics of Organizations His research employs advanced theoretical models to address questions in cooperative economies, contract theory, and market frictions. His recent publications, appearing in leading economics journals, reveal a consistent theme of applying microeconomic theory to diverse economic structures. Notably, his work spans cooperative economic growth, smart contracts in durable goods markets, and the analysis of frictions across multiple markets in European economies. These contributions highlight his expertise in dynamic general equilibrium and game-theoretic modeling. Regarding scientific recognition, no awards or fellowships were mentioned in the available information. Information about his student advising and research grants was not provided in the text.

Jingcun Caoمشاهده پروفایل

استادیار

• Mobile App Ecosystem
• Online Education
• Health Care
• +۹ مورد دیگر

Jingcun Cao is an Assistant Professor at the University of Hong Kong, where he joined in 2020. He holds a Ph.D. in Marketing from Indiana University, an M.A. in Economics and Business from the same institution, and a B.S. in Computational Mathematics from Xiamen University. He also completed visiting programs at the University of Chicago Booth School of Business and National Tsing Hua University. His research addresses mobile app ecosystems, online education, healthcare, digital marketing, and environmental policy. Methodologically, he specializes in causal inference, applied machine learning, randomized field experiments, and econometrics. His collaborations with tech firms focus on business intelligence and big data analytics. Teaching responsibilities include courses such as Big Data Marketing (MKTG 3530), Introduction to Marketing (MKTG 2501), and executive education modules in MarTech, Business Analytics, and Brand Management. His publications analyze trends in digital platform governance, deep learning applications for consumer behavior, socioeconomic impacts of policy interventions, and mobile app monetization strategies. Research consistently integrates multidisciplinary approaches to solve industry-relevant problems. He is currently recruiting Research Assistants and holds pending patents for machine-learning algorithms related to marketing analytics.

Daphne Ngar-yin Mahمشاهده پروفایل

دانشیار

• Smart energy transitions
• Comparative energy governance in Asia
• Smart grids
• +۷ مورد دیگر

Professor Daphne Ngar-yin Mah is an Associate Professor in the Department of Geography at Hong Kong Baptist University (HKBU) and serves as the Director of the Asian Energy Studies Centre. Named as one of the World's Top 2% Scientists by Stanford University in 2022, she has established herself as a leading expert in energy policy and governance in Asian contexts. Dr. Mah received her Ph.D. from The University of Hong Kong, M.Sc. from The University of Nottingham (UK), and BSSc from the Chinese University of Hong Kong. Her academic journey reflects a strong foundation in both geographical and energy studies with international perspectives. Her research focuses on the social dimensions of energy transitions, with particular expertise in smart grids, urban solar energy, energy communities, and comparative energy governance across Asian cities. Dr. Mah employs interdisciplinary approaches that bridge geography, policy studies, and energy technology assessment to examine how communities and institutions navigate the complex challenges of sustainable energy development. Her work often emphasizes participatory governance models and the role of social learning in energy transitions. Analysis of Dr. Mah's recent publications reveals a consistent focus on understanding the socio-political dimensions of energy transitions in Asian contexts. Her work spans multiple research streams including energy governance frameworks, community engagement in renewable energy adoption, energy poverty and justice issues, and regional energy collaboration in the Greater Bay Area. A distinctive feature of her research is the comparative approach, examining energy transitions across multiple Asian cities to identify transferable lessons and context-specific challenges. World's Top 2% Scientist (2022) (named by Stanford University) Faculty/School of Social Sciences Performance Award in Teaching (Team Teaching), HKBU (2024) Faculty Performance Award in Team Teaching 2023/24 (Faculty of Social Sciences Team) Performance Award in Scholarly Work for the Faculty of Social Sciences (2022), HKBU Faculty Award for Early Career Academic (Research)(2014), HKBU Chevening Scholarship Dr. Mah has demonstrated exceptional success in securing research funding, having led 32 research projects as principal investigator totaling over HK$11.4 million. Her grant portfolio includes significant awards from the Research Grants Council (including General Research Fund and Research Impact Grant projects), Greenpeace East Asia, the Chinese Academy of Engineering, and various government bodies. She has established strong collaborative networks across Asia and with international institutions, frequently working with researchers from Japan, South Korea, China, and Europe. Dr. Mah also serves as Chairperson of the Hong Kong Geographical Association (2023-2025) and is actively involved in community engagement through initiatives like the Hong Kong Solar Partnership. As Director of the Asian Energy Studies Centre, Dr. Mah leads a multidisciplinary research team focused on energy transitions in Asian contexts. She is also the founding convener of the Asian Low-Carbon Universities-Cities Network (ALUN), which connects academic institutions with city governments to accelerate low-carbon transitions. Through her role as co-founding editor of the Journal of Asian Energy Studies, she has helped establish an important platform for scholarly discourse on energy issues in the region.