جستجوی استاد راهنمای دانشگاهی

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.

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.

Anthony T.C. Tamمشاهده پروفایل

مدرس

• Cluster Computing
• Parallel Computing
• High-speed Communication
• +۲ مورد دیگر

Dr. Anthony T.C. Tam is a Lecturer and Academic Advisor at the School of Computing and Data Science, University of Hong Kong. He holds a BSc (First Class Honors) from Asia International Open University (formerly EAOI), MAppSc from Queensland University of Technology (Australia), and a PhD in Computer Science from HKU (2002). His research focuses on cluster computing, parallel computing, high-speed communication systems, and operating system performance analysis. Over his career, he has been recognized as an outstanding tutor for three consecutive years. His research emphasizes optimizing communication protocols and scheduling algorithms in distributed systems. Recent work includes studies on contention-aware scheduling, gigabit Ethernet-based supercomputing, and realistic communication modeling for clusters. He has contributed to both academic journals and international conferences on parallel and distributed computing systems. Dr. Tam actively advises students in computer science programs and participates in curriculum development. His technical expertise is showcased through his homepage (https://www.cs.hku.hk/~atctam) and publications accessible via institutional repositories. No scientific awards are explicitly mentioned in the provided information.

Yi-Teng Shihمشاهده پروفایل

استادیار

• Design Cognition
• Design Media
• Design Education
• +۵ مورد دیگر

Yi-Teng Shih is an Assistant Professor at the School of Design, The Hong Kong Polytechnic University, with expertise in design cognition, design media, and design education. He holds a PhD in Architecture from the University of Newcastle, Australia, and a PGCHE in Higher Education from the University of Nottingham, UK. Education: PhD (University of Newcastle, Australia), PGCHE (University of Nottingham, UK) His research explores the intersection of design cognition, computer-aided design, and user experience, with a focus on enhancing learning outcomes through collaborative design competitions and mental imagery analysis. His work has been published in journals like Design Studies and The Design Journal . Recent publications highlight trends in: Neuroscience-informed design teamwork (2025) Educational frameworks for ADHD children (2024) Conceptual metaphor in product language (2024) Digital and analog media in design education (2021–2017) Scientific Awards: THE EDTECH AWARDS 2025 – Finalist Animal Dough Hair Playset (IDEA, 2021) Baby Friendly Bathroom Fitting Series Design (European Product Design Award Gold, 2018) Best Conference Paper Award (2025) Business Casual Headset (IDA Design Awards Gold, 2018) He has supervised numerous award-winning design projects and collaborated with companies such as Brookstone, RadioShack, and FORA, securing twelve patents. His activities include organizing the PolyU Toy Invention Program (2023–2024) and delivering invited talks on design education.

Jing Liمشاهده پروفایل

مدرس ارشد

• Consumer Demand Modeling
• Industrial Organization
• Applied Econometrics
• +۵ مورد دیگر

Dr. Jing Li serves as Senior Lecturer and Deputy Programme Director for BBA (IBGM) at the University of Hong Kong's Faculty of Business and Economics, School of Economics and Finance. Her office is located in KK 938 with contact number 3917 0024. Her academic qualifications include a PhD in Applied Economics from The Pennsylvania State University, an MA in Finance from Central University of Finance and Economics, and a BA in Economics from China Youth University for Political Sciences. Prior to academia, she worked at Caterpillar (China) Financial Leasing Co., Ltd. Dr. Li's research centers on consumer demand determinants with emphasis on preference for variety and product health attributes. She investigates how product quality and productivity interact to shape firm competitiveness, particularly in sectors like food and steel industries. Her methodological expertise spans empirical industrial organization and applied econometrics using household-level purchase data and nutrition labeling information. Her publication trends reveal strong focus on practical economic applications: Recent thought leadership addresses US-China trade dynamics (H-1B visa policies, tariff wars), Chinese economic policy responses, and Hong Kong's tourism recovery. Earlier empirical work examines food insecurity patterns and ready-to-eat cereal market dynamics using advanced demand modeling techniques. Dr. Li actively contributes to academic discourse through industry-relevant publications while maintaining strong teaching commitments in Industrial Organization, Consumer Behavior, Business Strategy, and Chinese Economy courses. Her industry background informs practical pedagogy where she excels at simplifying complex phenomena through rich case studies.

Edmund Yin Mun LAMمشاهده پروفایل

استاد

• Computational Optical Imaging
• Digital Holography
• Neuromorphic Imaging
• +۳ مورد دیگر

Edmund Yin Mun LAM is a Professor of Electrical and Electronic Engineering at the University of Hong Kong (HKU), with a courtesy appointment in Computer Science. He also serves as Associate Dean (Innovation and Career Development) of HKU's Graduate School. His academic journey includes a B.S., M.S., and Ph.D. from Stanford University. Key roles include Director of the Computer Engineering program and founding Director of the Imaging Systems Laboratory. He has held a Visiting Associate Professorship at MIT. His research focuses on computational optics and imaging, spanning algorithm design to applications in semiconductor manufacturing and biomedicine. Notable contributions include pioneering AI-driven computational imaging and deep learning for holographic microscopy. Awards include the IBM Faculty Award and multiple HKU accolades. He is a Fellow of IEEE, Optica, SPIE, IS&T, IOP, and HKIE, and a founding member of the Hong Kong Young Academy of Sciences. Education: B.S., M.S., and Ph.D. in Electrical Engineering from Stanford University (1995–2000). Research Interests: Computational optical imaging, digital holography, neuromorphic imaging, biomedical imaging, AI integration in computational optics. His work bridges algorithmic innovation with practical applications, emphasizing cross-disciplinary solutions for imaging challenges in healthcare and engineering. Awards and Recognition: Over 400 publications, 30+ advised students, IBM Faculty Award, HKU Outstanding Researcher Award (2019), and multiple teaching awards. His research impacts fields like semiconductor lithography and medical diagnostics. Labs and Teams: Imaging Systems Laboratory (founded), Computer Engineering Program leadership, involvement in SPIE conference organization, and editorial roles in top journals like IEEE Transactions on Biomedical Circuits and Systems.

Heming Cuiمشاهده پروفایل

دانشیار

• Distributed Systems
• Operating Systems
• Cloud Computing
• +۷ مورد دیگر

Dr. Heming Cui is an Associate Professor at the Department of Computer Science, University of Hong Kong, affiliated with the School of Computing and Data Science. He joined HKU in 2015 after completing his PhD at Columbia University, following bachelor's and master's degrees from Tsinghua University. His research focuses on distributed systems, operating systems, and high-performance computing, with a strong emphasis on reliability and security. Dr. Cui leads projects in distributed AI training systems, blockchain frameworks, and secure execution environments, collaborating closely with industries like Huawei. He has received notable awards including the Croucher Innovation Award (2016), HK$5 million RGC Research Impact Fund (2023), and best paper awards at ICSE and ACSAC. His work has led to commercialized systems such as Huawei's MindSpore integration of Fold3D and TICS' UTEE component derived from his secure systems research. Dr. Cui actively recruits PhD students specializing in systems security and database systems, prioritizing candidates with strong systems-building backgrounds. Key grants include leadership in projects totaling HK$30 million, including flagship collaborations with Huawei and RGC grants targeting transaction/analytical processing in edge computing and cloud security. His research spans over 50 publications in top venues like SOSP, NSDI, and IEEE journals, emphasizing reproducibility and industrial impact.

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.

Sandra Marco Colinoمشاهده پروفایل

دانشیار

• Competition Law
• Merger Control
• Digital Economy
• +۶ مورد دیگر

Sandra Marco Colino is an Associate Professor at The Chinese University of Hong Kong (CUHK) Faculty of Law, specializing in competition law, merger control, digital economy regulation, and EU law. She joined CUHK in 2010 and serves as Deputy Programme Director of the Master of Laws (LLM) in International Economic Law. Her institutional affiliations include the International Competition Network (as Non-Governmental Advisor), the European University Institute’s Centre for a Digital Society (Scientific Committee), and the law firm Dictum (Academic Board). Her educational background includes: PhD, European University Institute, Florence LL.M., Universidad Carlos III, Madrid Law Degree, Universidad San Pablo CEU, Madrid Postgraduate Certificate in Academic Practice, University of Glasgow Prof. Marco Colino’s research focuses on the intersection of antitrust policy, digital markets, and regulatory frameworks. She examines how competition law adapts to technological disruptions, with particular emphasis on platform economies, vertical restraints, and cross-jurisdictional enforcement challenges. Her work bridges theoretical legal analysis with practical regulatory applications, especially in Asian and EU contexts. She founded the Communications Policy and Regulation Scholars Forum (CPRSF) in 2010 to foster academic-practitioner dialogue. Her publications reveal evolving expertise from foundational EU competition law to cutting-edge digital antitrust issues. Recent work explores environmental and social dimensions of competition policy (“Green Antitrust”), platform regulation in China, and the global ripple effects of antitrust enforcement. Her scholarship consistently addresses regulatory gaps in emerging markets while maintaining rigorous comparative analysis. Notable recognitions include: Young Researcher Award (CUHK, 2021) Academic Excellence Award (Global Competition Review, 2020) Antitrust Writing Award (Concurrences, 2018) Teaching Excellence Award (CUHK, 2017) Georgetown University Award for Best Paper (2004) She actively mentors doctoral candidates on topics including Nigerian electricity liberalization, China-EU economic relations, and data protection. As Principal Investigator for three major Hong Kong Research Grants Council projects, she leads empirical work on cartel detection in Hong Kong/China and telecommunications regulation. Her collaborative EU-funded Jean Monnet networks advance transnational competition policy dialogue. She previously directed CUHK’s Centre for Financial Regulation and Economic Development (2014-2021) and co-founded Hong Kong’s European Union Academic Programme.

Paolo Mengoniمشاهده پروفایل

مدرس

• Artificial Intelligence
• Complex Network Analysis
• Natural Language Processing
• +۳ مورد دیگر

Dr. Paolo Mengoni is a Lecturer I at Hong Kong Baptist University (HKBU), specializing in Artificial Intelligence and Complex Network Analysis. Originally from Italy, he brings over 20 years of experience as an IT consultant and researcher. His work focuses on AI applications in education, natural language processing, emotion recognition, and autonomous agents. He holds a Ph.D. in Computer Science from the University of Florence and MSc/BSc degrees from the University of Perugia (Italy). Teaching responsibilities include courses like AI and Digital Communication , Basic Programming for Data Science , and Recommender Systems for Digital Media . His research explores topics such as learning analytics, sentiment analysis in social networks, and community detection in collaborative environments. He actively contributes to academic activities, including organizing international workshops like the 2020 Global Virtual Hack and Design Challenge and the HKBU-University of Perugia exchange program. His publications span journals and conferences including IEEE/WIC/ACM Web Intelligence, Future Generation Computer Systems, and IEEE International Symposia. He serves as a reviewer for venues such as IEEE Congress on Evolutionary Computation and the International Conference on Computational Science and Its Applications.

• Visual Arts
• Creative Entrepreneurship
• Sustainable Design

QIN Lai Yin Anna serves as an Assistant Professor in the Academy of Visual Arts at the School of Creative Arts, Hong Kong Baptist University, where she bridges artistic practice with sustainable innovation and entrepreneurial frameworks. Her research program integrates three interconnected domains: Visual Arts : Contemporary artistic methodologies and cultural discourse analysis Creative Entrepreneurship : Business model development for artist-led enterprises Sustainable Design : Eco-conscious material systems and production processes in visual culture

• Journalism curriculum
• Education
• Journalism education
• +۸ مورد دیگر

Robin Ewing serves as Senior Lecturer and Director in the Department of Journalism at Hong Kong Baptist University's School of Communication, where she leads academic strategy and curriculum development for journalism education in Hong Kong's dynamic media landscape. Her research and teaching expertise spans journalism curriculum design, digital journalism evolution, and practical training methodologies. Key focus areas include student media operations, internship program development, longform journalism techniques, news and feature writing pedagogy, international journalism frameworks, and Hong Kong-specific media analysis. Her work emphasizes bridging theoretical knowledge with real-world journalistic practice in rapidly changing media environments. As Director, she oversees departmental operations while maintaining active teaching responsibilities. Her email contact is ewing@hkbu.edu.hk with office telephone 34112547, reflecting her ongoing engagement with students and academic administration at HKBU.

Yang Liuمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +۸ مورد دیگر

Dr. Yang Liu is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University's Faculty of Science. He also serves as the Associate Director of the Health Informatics Center. His academic career spans prestigious institutions including Yale University and Carnegie Mellon University, demonstrating his expertise in both theoretical and applied aspects of computer science. Dr. Liu received his B.Eng. and M.Eng. degrees in Automation from National University of Defense Technology in 2004 and 2007, respectively. He earned his Ph.D. in Computing from The Hong Kong Polytechnic University in 2011. His academic journey included a Visiting Scholar position at Carnegie Mellon University's Robotics Institute (Feb.-Aug. 2010) and a Postdoctoral Research Associate position in the Department of Statistics at Yale University (2011-2012). Dr. Liu's research spans the intersection of artificial intelligence, machine learning, and practical applications in health and complex systems. His work focuses on artificial intelligence , machine learning , pattern recognition , dimensionality reduction , and subspace learning , with particular emphasis on multi-way/multi-view/multi-label/multi-task learning approaches. His research extends to modeling complex dynamical systems with applications in computational epidemiology and infectious disease modeling , addressing critical public health challenges through data-driven approaches. Analysis of Dr. Liu's recent publications reveals a strong focus on applying machine learning techniques to epidemiological challenges, particularly in modeling infectious disease transmission patterns. His work bridges theoretical advances in graph neural networks, subspace learning, and multi-view analysis with practical applications in public health. A significant portion of his research addresses the challenges of high-dimensional and heterogeneous data analytics, with applications ranging from malaria transmission modeling in Cambodia to uncovering COVID-19 transmission patterns in Hong Kong. Dr. Liu is an IEEE Senior Member and ACM Member, reflecting recognition of his contributions to the field. His paper "What are the underlying transmission patterns of COVID-19 outbreak? – An age-specific social contact characterization" was recognized as one of the most cited articles in EClinicalMedicine, Lancet Discovery Science, during 2020-2021, highlighting the impact of his work on pandemic response research. Dr. Liu actively mentors research students and regularly has research student and RA positions available. His professional service includes serving on editorial boards for SPJ Health Data Science and as a journal guest editor for special issues on cross-media analysis. He has extensive experience as a journal reviewer for top publications including IEEE TNNLS/TNN, IEEE T-Cyber/TSMC-B, IEEE TAC, IEEE TKDE, IEEE TMM, IEEE TCSVT, ACM TIST, ACM TOMM, and others, and serves on program committees for major conferences including WWW, IJCAI, and AAAI. Dr. Liu is affiliated with the Centre for Health Informatics and the Artificial Intelligence and Machine Learning Laboratory (AIML) at Hong Kong Baptist University. These research centers provide the infrastructure and collaborative environment necessary for his work in health informatics and machine learning applications. His role as Associate Director of the Health Informatics Center positions him at the forefront of interdisciplinary research connecting computing with public health challenges.

Xin WANGمشاهده پروفایل

استاد

• Financial reporting quality
• Management earnings forecasts
• Sell-side analysts
• +۲ مورد دیگر

Professor Xin WANG serves as Professor and Head of the Accounting and Law Area at The University of Hong Kong (HKU), where he has been faculty since 2011 after previously teaching at The Chinese University of Hong Kong (CUHK). Promoted to full Professor in 2019, he holds leadership roles including Chairman of the Departmental Research Postgraduate Committee and Faculty Review Committee. His academic credentials include: PhD in Accounting, Duke University, Durham NC, USA MS in Accounting, Tsinghua University, Beijing, China BA in Accounting, Tsinghua University, Beijing, China WANG's research examines financial reporting quality , management earnings forecasts , sell-side analyst behavior , corporate governance structures , and insider trading dynamics . His work investigates how information asymmetry impacts capital markets through rigorous empirical analysis of disclosure practices, governance mechanisms, and regulatory environments. He has published extensively in premier journals including The Accounting Review and Journal of Accounting and Economics . His 12 most recent publications (2006-2022) reveal consistent focus on governance-tax planning interactions, site visit information transmission, political uncertainty effects, and market efficiency. Methodologically, he employs large-scale datasets with advanced econometric techniques to analyze financial reporting quality across international contexts and corporate structures. His scholarly recognition includes: Best Paper Award at The Sixth Annual Research Conference of CAPANA (2013) Best Paper Award at the American Accounting Association International Section Midyear Meeting (2010) WANG teaches across HKU's academic programs including undergraduate Intermediate Financial Accounting and Master of Accounting Management Accounting courses. His administrative leadership in Faculty Higher Degrees and Research Committees demonstrates commitment to academic governance. While specific grant details aren't provided, his publication volume indicates substantial research funding support for empirical accounting studies.

HAO Puمشاهده پروفایل

دانشیار

• Urban geography
• Migration and mobility
• Platform economy
• +۱ مورد دیگر

HAO Pu is an Associate Professor in the Department of Geography at Hong Kong Baptist University, serving as Programme Director for the BSocSc (Hons) in Geography and participating in committees for the MSocSc in Contemporary China Studies and MA in Global Society programmes. Education: Ph.D., Utrecht University, Netherlands M.Sc., International Institute for Geo-Information Science and Earth Observation (ITC), Netherlands M.Eng. and B.Eng., Wuhan University, China His research centers on urban geography with critical focus on migration/mobility dynamics, platform economy impacts, and urban housing challenges in China. He investigates how rural landholdings influence migrant mobility decisions, the spatial organization of informal economies, and socio-spatial segregation patterns in rapidly urbanizing contexts like Shenzhen and Nanjing. His methodological approach combines quantitative spatial analysis with qualitative fieldwork to examine policy implications for inclusive urban development. Recent publications (2024-2016) reveal consistent thematic evolution from urban village studies toward gig economy labor dynamics, showing increasing emphasis on digital platforms' role in reshaping migration patterns and housing markets. His work demonstrates strong regional focus on Jiangsu, Nanjing, and Beijing while engaging with global urban theory through China-specific cases. Scientific Awards: Lincoln Institute of Land Policy China Program International Fellowship (2016-2017) As Principal Investigator, he has secured substantial competitive funding including multiple RGC General Research Fund and Early Career Scheme grants, National Natural Science Foundation of China projects, and internal HKBU research awards. His current work examines rural migrant workers' experiences in China's gig economy through a HK$1.17 million RGC grant (2023-2025).