جستجوی استاد راهنمای دانشگاهی

Tobias Kleinمشاهده پروفایل

دانشیار

• Digital Craft
• 3D Printing
• Architecture
• +۶ مورد دیگر

Tobias Klein is an Associate Professor at the School of Creative Media, City University of Hong Kong. He is an internationally recognized architect and interdisciplinary artist whose work bridges the fields of art, installation, experimental design, interactivity, and sculpture. His practice operates at the intersection of digital and physical creation, exploring new territories in narrated embodied space. Klein's research focuses on Digital Craft as an operational synthesis between digital and physical materials and tools as poetic (Poïesis) and technical (Technê) expressions. His work challenges the traditional dualistic separation of digital workflows and analog making, instead creating a confluence where techniques and concepts are symbiotically intertwined. Key research areas include 3D modeling and printing, augmented reality, installation art, and the application of advanced medical visualization techniques to explore the human body as a new ecology of densities. His recent artistic output reveals a strong trend toward environmental reactivity and material hybridization, with works like Common Datum exploring invisible forces and their physical manifestations. Klein's publications demonstrate an increasing focus on interdisciplinary approaches that combine traditional craftsmanship with digital fabrication, particularly in glass and ceramics, while also exploring blockchain applications for representing human values. SCM Research Award 2018 SIGGRAPH 2018 - Best Art Paper Award Klein actively supervises PhD students including Hin Nam FONG, Zidong HUANG, Hoi Ching MOK, Pierre Yat Siu SHUM, and Daniel STEMPFER. His current research projects include Hybrid Glass Craft, Science + Technology + Arts (START), and Material and Fabrication in and for the Ocean, demonstrating his commitment to interdisciplinary approaches that merge art, technology, and cultural heritage. His studio practice maintains a fascination with the construct of space while questioning modern understandings of embodiment, perception, and projection.

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.

• Quantum Information Theory
• Quantum Cryptography
• Quantum Computation
• +۲ مورد دیگر

Professor Hoi Fung Chau is a theoretical quantum information scientist at the Department of Physics, Faculty of Science, The University of Hong Kong. With a research focus spanning quantum cryptography, quantum computation, and quantum speed limits, his work bridges rigorous mathematical proofs with practical innovations like satellite-to-ground communication patents. Education: B.Sc. (1989) and Ph.D. (1992) from HKU Research Interests: His research primarily explores: Quantum speed limits for information processing Secure key rate optimization in quantum cryptography Quantum information theory fundamentals Theoretical astrophysics applications Recent Research Trends: His 15 most recent publications focus on quantum communication protocols, speed limit theory, and atmospheric distortion mitigation in satellite links. These works span mathematical physics foundations, practical quantum network engineering, and statistical frameworks for finite-key analysis. Awards: Outstanding Referee, American Physical Society (2009) Grants & Collaborations: Currently leading General Research Fund projects on quantum speed limits and depolarization security, while maintaining extensive collaborations across Hong Kong-Shenzhen quantum research workshops and ERATO conferences.

• Computational condensed matter physics
• Large-scale high-performance quantum computations
• New paradigms in quantum matter
• +۶ مورد دیگر

Professor Zi Yang Meng is a theoretical and computational physicist at the Department of Physics, University of Hong Kong , with prior affiliation at the Institute of Physics, Chinese Academy of Sciences . He earned a B.Sc. from University of Science and Technology of China , and M.Sc. and Ph.D. from University of Stuttgart , followed by postdoctoral work in the US and Canada. His research focuses on quantum many-body simulations to study quantum materials, topological phases , and entanglement phenomena . His work spans quantum phase transitions , non-Fermi liquid behavior , and dynamical signatures in quantum magnets , with over 140 publications and ~7000 citations. He develops numerical methods for constrained lattice models and Rydberg atom arrays , addressing challenges in high-temperature superconductivity and quantum computer building blocks . Recent grants include Collaborative Research Fund (CRF) 2022/23 and General Research Fund (GRF) projects for quantum moiré materials and entanglement computation . Research Grants: CRF C7037-22G (2022): Many-body paradigm in quantum moiré material research GRF 17302223 (2023): Novel phases of Rydberg arrays GRF 17301924 (2024): Precise computation of quantum entanglement Supervision: PhD students in computational quantum physics, 2D materials, and condensed matter theory Projects on topics like fractional Chern insulators , dimension-tunable quantum systems , and disorder operators Collaborations: Prof. Kai Sun (University of Michigan) Prof. Han-Qing Wu (Sun Yat-sen University) International teams from CUHK, Yale, UCSB, and German institutions He actively contributes to knowledge exchange via public lectures and science communication , and serves on editorial boards for journals like Reports on Progress in Physics . Upcoming conferences include "Fractional Chern Insulators: Theory, Numerics, and Experiment" (2025) at HKU, where he chairs the organizing committee.

Yi Maمشاهده پروفایل

استاد

• Computer Vision
• High-Dimensional Data Analysis
• Intelligent Systems
• +۳ مورد دیگر

Yi Ma is a Professor of Computer Science at the University of Hong Kong (HKU), serving as Chair of Artificial Intelligence and Director of HKU's School of Computing and Data Science (HKU CDS) and the Musketeers Foundation Institute of Data Science (HKU IDS). He holds a joint faculty position in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. His academic journey includes roles at UIUC (2000-2011), Microsoft Research Asia (2009-2014), and ShanghaiTech University (2014-2017). He earned his PhD from UC Berkeley in 2000, with earlier degrees from Tsinghua University. Research focuses on computer vision, high-dimensional data analysis, and intelligent systems, with contributions to robust face recognition, sparse representation, and deep learning principles. Key publications include works on ReduNet, low-dimensional models, and generalized PCA. He has been Program Chair for ICCV 2013 and General Chair for ICCV 2015. Recent activities include keynote speeches at international conferences (e.g., Future Science Prize Symposium 2024, PRCV 2024) and leadership in initiatives like the Conference on Parsimony and Learning (CPAL 2024). Awards include IEEE, ACM, and SIAM Fellowships, along with best paper and Marr prizes. Education : Bachelor’s in Automation and Applied Mathematics, Tsinghua University (1995) Master’s in EECS and Mathematics, Tsinghua University (1997) PhD in EECS, UC Berkeley (2000) Awards : NSF Career Award (2004) ONR Young Investigator Award (2005) David Marr Prize (ICCV 1999) IEEE/ACM/SIAM Fellowships Labs & Initiatives : HKU IDS and CDS Berkeley Artificial Intelligence Research (BAIR)

Xiaojuan Qiمشاهده پروفایل

استادیار

• 3D Vision
• Deep Learning
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Xiaojuan Qi is an Assistant Professor in the Department of Electrical and Electronic Engineering at The University of Hong Kong. Her research focuses on 3D vision, deep learning, and AI applications in medical imaging and science. She holds memberships in IEEE and CCF. Education: PhD, The Chinese University of Hong Kong (2018) BEng, Shanghai Jiao Tong University (2014) Postdoctoral Researcher, University of Oxford (prior to HKU) Research Interests: Dr. Qi develops scalable deep learning algorithms for medical and natural image analysis, 3D scene understanding, and neural network behavior in out-of-distribution scenarios. Her work emphasizes label efficiency, geometric reasoning, and cross-modal integration. Lab Contributions: As head of the Computer Vision and Machine Intelligence Lab (CVMI Lab), she explores open-world intelligence, 3D reconstruction, and AI applications in robotics, autonomous systems, and healthcare. Recent lab highlights include 10+ ICCV/CVPR/NeurIPS papers in 2023-2025. Awards: ImageNet Semantic Parsing Challenge (1st Place) Outstanding Reviewer Awards (ICCV 2017/2019) CVPR Doctoral Consortium Travel Award Advising & Grants: Supervises ~20 PhD students (listed in detail). Active in securing grants for embodied AI, medical imaging, and edge computing hardware. Lab Collaborations: Focuses on interdisciplinary projects with Intel, Oxford, and Toronto groups, emphasizing 3D vision, neuromorphic computing, and AI-driven medical solutions.

Dong Xuمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Multimedia
• +۴ مورد دیگر

Professor Dong Xu is a faculty member at the University of Hong Kong's School of Computing and Data Science, Department of Computer Science. He holds a PhD from the University of Science and Technology of China (USTC). His research focuses on computer vision, multimedia, and machine learning, with applications in autonomous driving, AR/VR, medical image analysis, and video surveillance. He has published over 150 papers in top venues like CVPR, ICCV, and IEEE Transactions. He has received prestigious awards including IEEE and IAPR Fellowships, and holds editorial roles at ACM Computing Surveys and multiple IEEE Transactions journals. Education: B.Eng. and PhD from USTC (2001, 2005). Postdoctoral work at Columbia University, tenure-track roles at Nanyang Technological University and the University of Sydney. Current research includes developing machine learning methods for vision and multimedia systems. His publications emphasize cross-domain adaptation, neural networks for video analysis, and medical imaging. Recent work explores spatial-temporal modeling, adversarial learning, and generative AI in HCI. Leadership roles include Program Coordinator for ACM Multimedia 2024, steering committee member for ICME, and program co-chair for multiple conferences. Awards highlight his editorial contributions and research impact in pattern analysis. Advising: Supervised students whose work earned Best Student Paper (CVPR 2010) and IEEE Prize Paper (2014). Active in organizing international conferences and training future researchers.

Chao Huangمشاهده پروفایل

استادیار

• Large Language Models
• Graph Learning
• Recommender Systems
• +۳ مورد دیگر

Chao Huang is an Assistant Professor at the Department of Computer Science and Institute of Data Science at the University of Hong Kong (HKU). As the director of the Data Intelligence Lab@HKU, his research focuses on Large Language Models (LLMs), LLM Agents, Graph Learning, Recommender Systems, and AI for Smart Cities. He holds a PhD from the University of Notre Dame. Education: PhD in Computer Science from University of Notre Dame (USA). Research Interests: His work bridges machine learning with practical applications, including: Developing advanced LLM frameworks like GraphGPT and UrbanGPT Creating automated research tools (AutoAgent, AI-Researcher) Designing recommendation systems with LLM integration (RLMRec, LLMRec) Exploring spatio-temporal AI for urban challenges Notable Achievements: Over 11,000 Google Scholar citations (h-index 55), multiple top conference awards (WWW/SIGIR/KDD), and open-source projects with thousands of GitHub stars. His work has been recognized as most influential/pioneering in major AI conferences. Labs/Teams: Leads the Data Intelligence Lab, collaborating on projects like LightRAG, MiniRAG, and VideoRAG. The lab emphasizes open-source contributions with repositories on GitHub. Grants/Advising: Supervises PhD/MPhil students and offers research internships. Active in recruiting motivated researchers and students through HKU's programs.

Ruibang Luoمشاهده پروفایل

دانشیار

• Bioinformatics
• Clinical Informatics
• Genomics
• +۲ مورد دیگر

Ruibang Luo is an Associate Professor in the Department of Computer Science at the School of Computing and Data Science, University of Hong Kong, and serves as Assistant Director (Learning Experience & Student Enrichment). His research spans bioinformatics algorithms and clinical informatics, with over 80 publications including ten highly cited papers. \n His educational background includes: \n \n PhD in Bioinformatics from the University of Hong Kong (2010-2015) under Dr. Tak-Wah Lam \n Postdoctoral training at Johns Hopkins University (2016-2017) with Drs. Steven Salzberg and Michael Schatz \n \n Luo's research centers on bioinformatics and clinical informatics , developing algorithms for genomic data analysis. Key areas include variant calling, metagenomics assembly, pan-genome construction, and AI applications in precision medicine. His work bridges computational methods with clinical solutions for genomic surveillance and disease detection. \n Analysis of his recent publications (2021-2022) reveals strong focus on population genomics (Hong Kong Cantonese exomes, Chinese pan-genome), nanopore sequencing for epigenomics/transcriptomics, and AI-driven gene-disease relation extraction. Earlier work established foundational tools like MEGAHIT for metagenome assembly and SOAPdenovo for genome alignment. \n Luo has received significant recognition: \n \n Top 1% Scholars Worldwide by Clarivate Analytics (2019-2023) \n Baidu Research: Worldwide Top 150 Chinese Young Scholars in AI \n MIT Technology Review: Top 10 Innovators Under 35 Asia Pacific (2019) \n Forbes: 30 Under 30 Asia in Healthcare and Science (2017) \n \n As principal investigator, Luo secured grants including RGC GRF for cancer mutation detection using single-molecule sequencing and industrial collaboration with Oxford Nanopore Technologies. He contributed as Co-PI to cardiovascular risk prediction and automated karyotype analysis projects. His group actively translates bioinformatics algorithms into clinical applications through partnerships with medical institutions. \n Luo leads a research team within HKU's Department of Computer Science focused on next-generation bioinformatics tools for clinical genomics, with ongoing work expanding Chinese pan-genome resources and AI diagnostic systems.

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.

Jaehyun Jaden Parkمشاهده پروفایل

دانشیار

• UX & Service Design
• Entrepreneurship
• Digital Innovation
• +۱۳ مورد دیگر

Jaehyun Jaden Park is an Associate Professor at the School of Design within the Hong Kong Polytechnic University , specializing in UX & Service Design , Entrepreneurship , and Digital Innovation . He leads interdisciplinary research bridging business, design, and technology to address human-centered challenges in smart systems and innovation. Education: PhD in Management, Case Western Reserve University MDes in Design Planning & Communication, Illinois Institute of Technology BFA in Painting & Design, Seoul National University BFA in Korea Printing, Seoul National University His research explores interdisciplinary intersections , including: Human-enterprise relationships in design, innovation, and technology Smart systems for aging populations and accessibility Metaverse engagement and representational fidelity Design-driven entrepreneurship methodologies Recent research trends highlight service robots , AI applications , and metaverse sociability . His grants include HK$ 1,203,180 for cross-cultural robot studies and JSPS grants exceeding 10 million yen for digital innovation projects. Scientific Awards: Osaka International Concept Design Award (2024) Best Research Award from KMIS International Conference (2021) AIS Research Award (JASMIN 2015, 2016) Second Prize at Financial Security Paper Contest (2010) Dr. Park actively collaborates with academic and industry partners, serving as Principal Investigator for grants related to smart tourism , design research , and AI accessibility . He currently seeks PhD students and research assistants for his interdisciplinary team.

Clifford Sze Tsan Choyمشاهده پروفایل

مدرس ارشد

• Interaction design
• Physical computing
• Digital fabrication
• +۴ مورد دیگر

Clifford Sze Tsan Choy is a Senior Lecturer at the School of Design, The Hong Kong Polytechnic University, specializing in interaction design, physical computing, and digital fabrication. Since 2000, he has contributed to design education and research while actively promoting maker culture through events like Maker Faire Hong Kong (2015, 2017, 2018). BEng (Hons) in Electronic Engineering, The Hong Kong Polytechnic University PhD, The Hong Kong Polytechnic University His research integrates digital fabrication with design knowledge management , focusing on creativity support systems and maker culture. Recent projects include thermal deformation analysis in 3D printing and sustainable molded pulp product fabrication. Dr. Choy's work spans design theory , applied technology , and interdisciplinary innovation , with publications addressing inclusive design for visually impaired users and fractal analysis in motor control studies. His research methodology emphasizes computational approaches to visual communication design. Professional engagements include membership in the CDC-HKEAA committee on Design and Applied Technology, and consultancy roles in robotics education programs. He leads initiatives on online collaborative design platforms and drink carton recycling education.

Zhou Zhibinمشاهده پروفایل

دانشگاهی

• Human-AI Interaction
• Design Methodology for AI-enhanced UX
• Human-Computer Interaction
• +۶ مورد دیگر

Dr. Zhou Zhibin is a Research Assistant Professor in the School of Design at The Hong Kong Polytechnic University . He is also a member of the Research Centre for Deep Tech Translation (RCDTT) and the PolyU Academy for Interdisciplinary Research . His expertise lies in Human-AI Interaction and Design Methodology for AI-enhanced UX , with a strong foundation in human-computer interaction and artificial intelligence. Education: He earned his PhD in Design Science from Zhejiang University School of Computer Science and Technology . He was also a visiting PhD candidate at Politecnico di Milano , where he worked on an AI-powered platform for package designers. Research Interests: Dr. Zhou's research focuses on Human-AI Interaction , Design Methodology for AI-enhanced UX , Machine Learning , Generative AI , Virtual Reality , and User Experience Design . His work explores the intersection of AI and design, aiming to create transparent and user-friendly AI systems. Research Trends: His recent publications (2021-2025) emphasize transparent AI agents , ML lifecycle tools , generative AI in UX design , and virtual reality applications . These works highlight his commitment to advancing AI-driven design methodologies and improving user experiences through innovative technologies. Consultancy: In 2023, he led a consultancy project on Interaction Design for the Digital Twin for Autonomous Tower Crane . Labs & Teams: He is affiliated with the Research Centre for Deep Tech Translation (RCDTT) and the PolyU Academy for Interdisciplinary Research , fostering interdisciplinary collaboration in AI and design.

Christopher Robertsمشاهده پروفایل

دانشیار

• Legal History
• British Empire
• International Institutions
• +۵ مورد دیگر

Christopher Roberts serves as Associate Professor at The Chinese University of Hong Kong's Faculty of Law, holding leadership roles as Deputy Director of the LLM Programme (Legal History) and Chair of the Transnational Legal History Group. He maintains external affiliations as Associate Research Fellow at the University of London's Institute for Commonwealth Studies and Editorial Board member for Constitutional Studies. His academic credentials include a JSD and JD from NYU School of Law, MA from the School of Oriental and African Studies, and BA from Brown University, with admission to the New York State Bar. These qualifications underpin his transnational legal expertise spanning academia and practice. Professor Roberts' research critically examines legal history of the British Empire, focusing on labor coercion, human rights evolution, and repressive governance during the First World War and interwar periods. His work bridges Legal History, British Empire studies, International Procedural Law, and Labor Law, revealing how colonial legal mechanisms shaped modern international norms through detailed analysis of vagrancy laws, forced labor definitions, and emergency powers. His 2019-2025 publications demonstrate consistent scholarly impact across top law journals, showing increasing integration of historical analysis with contemporary human rights challenges. Key trends include decolonizing labor law historiography, examining transnational repression models, and exploring procedural innovations in human rights bodies - all reflecting his dual commitment to academic rigor and practical legal reform. Scientific Awards: No formal awards documented in source materials Research funding highlights include two General Research Fund (GRF) projects: 'The Origins of Development: Anti-Colonial Resistance, Social Struggles and Labor Reform in the Interwar British Empire' and 'Empire, Internationalism and Global Labor Governance in the Inter-War Period', plus an Early Career Scheme (ECS) grant for 'The Exportation and Evolution of Vagrancy Laws in the Nineteenth Century British Empire'. His administrative contributions as former Assistant Dean for Undergraduate Studies and current LLM leadership demonstrate significant institutional engagement. He directs the Transnational Legal History Group at CUHK while maintaining active collaboration with international bodies including the African Commission on Human and Peoples' Rights, where his 'Guidelines on Freedom of Association and Assembly in Africa' achieved formal adoption in 2017.

Marius Hofertمشاهده پروفایل

دانشیار

• Dependence Modeling
• Computational Statistics
• Quantitative Risk Management
• +۳ مورد دیگر

Marius Hofert serves as Associate Professor of Statistics in the Department of Statistics and Actuarial Science at The University of Hong Kong's School of Computing and Data Science, with office in Room 228 of the Run Run Shaw Building. His research fundamentally addresses statistical dependence structures and computational methodologies for risk assessment. His core research domains include: Copula theory and dependence modeling for complex stochastic systems Advanced Monte Carlo and quasi-random sampling techniques Quantitative risk management frameworks for financial and insurance applications Recent publications demonstrate increasing integration of machine learning with traditional statistical methods, particularly through generative neural networks for dependence modeling. His critical examinations of AI tools like ChatGPT in quantitative contexts reveal methodological pitfalls while exploring new computational frontiers. As Academic Adviser in Risk Management, he mentors PhD candidates with strong mathematical backgrounds. He actively develops open-source statistical software through R packages including copula , nvmix , and qrmtools , maintaining the Quantitative Risk Management tutorial website (qrmtutorial.org).