جستجوی استاد راهنمای دانشگاهی

• Big Data
• Business Analytics
• Healthcare Analytics
• +۴ مورد دیگر

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

Xihui Liuمشاهده پروفایل

استادیار

• Computer Vision
• Generative Models
• Multimodal AI
• +۴ مورد دیگر

Xihui Liu is an Assistant Professor at the Department of Electrical and Electronic Engineering (EEE) and Institute of Data Science (IDS), The University of Hong Kong, with a courtesy appointment in the Department of Computer Science. She holds a PhD from the Chinese University of Hong Kong and a bachelor’s from Tsinghua University. Her research focuses on generative models, multimodal AI, computer vision, and their applications in embodied AI and AI for Science. Education: PhD in Multimedia Lab (MMLab), Chinese University of Hong Kong (2017–2021) Bachelor’s in Electronic Engineering, Tsinghua University (2013–2017) Research Interests: Generative models for 3D content and multimodal systems Embodied AI and vision-language integration Applications in scientific domains Awards: Adobe Research Fellowship (2020) Rising Stars in EECS (2021) WAIC Rising Stars Award (2022) Her work emphasizes interactive generative systems and benchmarks like T2I-CompBench. She co-organized workshops on multimodal foundation models and embodied AI, and currently serves as Area Chair for CVPR, NeurIPS, and ICLR.

Chu (Ivy) Dangمشاهده پروفایل

استادیار

• quantitative marketing
• economics of information
• consumer search
• +۹ مورد دیگر

Professor Chu (Ivy) Dang is an Assistant Professor of Marketing at the Business School of The University of Hong Kong, where she has been teaching since 2020. Her research focuses on the economics of information in quantitative marketing, examining how consumers search for information, how this information influences their choices, and the information provision strategies of firms in digital environments. Business School, The University of Hong Kong Assistant Professor of Marketing Specializes in consumer behavior in digital contexts Professor Dang received her Ph.D. in Marketing from The Chinese University of Hong Kong, where she also earned an M.S. in Economics. Her undergraduate degree is a B.S. in Applied Physics from Beijing Jiaotong University. Prior to her business studies, she spent two years conducting research in quantum information at RB Liu Lab as a Hong Kong PhD Fellowship Scheme (HKPFS) candidate in physics. Her research spans multiple dimensions of consumer behavior in digital environments, with particular emphasis on consumer search behavior and information economics. She investigates how consumers acquire and process information in online contexts, with applications to social media marketing where she examines the effects of Marketer-Generated Content (MGC), User-Generated Content (UGC), and increasingly, AI-Generated Content (AIGC). Her work on emerging trends in live-commerce and influencer marketing has provided new insights into how these formats reshape consumer decision processes. Analysis of her publications reveals a consistent focus on empirical methods to study information economics, with increasing attention to social media dynamics and emerging e-commerce formats. Professor Dang has secured significant research funding as Principal Investigator, including a General Research Fund grant (#17506824) and an Early Career Scheme grant (#27504221) from the Hong Kong Research Grants Council. She also leads projects funded by the HKU Business School Shenzhen Research Institutes and the HKU Seed Fund for Research. She recently co-organized the 14th Consumer Search and Switching Costs Workshop in Hong Kong in June 2025, demonstrating her leadership in this specialized research area. Her research has been published in top-tier journals including Journal of Marketing Research, Information Systems Research, and Marketing Science. Her teaching portfolio includes Social Media Marketing at both undergraduate and Master's levels, where she brings her cutting-edge research insights into the classroom to prepare students for the rapidly evolving digital marketing landscape. In her personal time, Professor Dang enjoys running, hiking, and spending time with her family.

Ka Ho Chowمشاهده پروفایل

استادیار

• Machine Learning
• Cybersecurity
• Artificial Intelligence
• +۶ مورد دیگر

Ka Ho Chow is an Assistant Professor in the Department of Computer Science at the University of Hong Kong, part of the School of Computing and Data Science. He holds a PhD from Georgia Institute of Technology and was previously a research scientist at IBM Research. His research focuses on the intersection of machine learning, cybersecurity, and scalable systems, emphasizing trustworthy AI and defense against security/privacy threats in federated learning, large language models, and visual recognition systems. Key achievements include IBM PhD Fellowship (2022) and Croucher Scholarship (2021). Education: PhD in Computer Science from Georgia Tech (2020), advised by Prof. Ling Liu. His work spans algorithmic optimization, infrastructure resilience, and adversarial machine learning. Current research explores attack-resilient solutions for centralized/federated learning and AI system vulnerabilities. Recent articles highlight innovations in federated learning security, gradient inversion attacks, backdoor detection, and privacy-preserving techniques. He has openings for PhD students interested in AI security and trustworthy systems. His lab collaborates on projects involving blockchain fraud detection (ZipZap), facial recognition privacy (Personalized Masks), and graph neural network robustness. Awards: IBM PhD Fellowship (2022), Croucher Scholarship (2021). Active in guiding PhD candidates and advising on microservices cloud migration (Atlas/SCAD systems). Research outputs include over 30 peer-reviewed papers spanning cybersecurity, AI ethics, and distributed learning frameworks.

Gerhard Bruynsمشاهده پروفایل

دانشیار

• Urban Morphology
• Spatial Design
• Interior Architecture
• +۷ مورد دیگر

Dr. ir. Gerhard Bruyns is a tenured Associate Professor at the School of Design, The Hong Kong Polytechnic University , where he serves as Associate Dean (Academic Programmes) and Director of RPg Studies . Previously, he held tenured positions at the Delft University of Technology , Netherlands, in both the Delft School of Design and the Department of Urbanism. His expertise spans spatial morphology, volumetric urbanism, and critical environments in dense urban contexts.

Ryo Ikeshiroمشاهده پروفایل

استادیار

• Sound Art
• Sonification
• Computational Creativity
• +۳ مورد دیگر

Ryo Ikeshiro is an Assistant Professor at the School of Creative Media, City University of Hong Kong, and co-director of the spatial audio art/research unit SoundLab. His work bridges sound art, computational creativity, and cultural studies through immersive installations, algorithmic audio-visual systems, and sonification techniques. PhD in Creative Practice (Goldsmiths, University of London) MPhil in Music (University of Cambridge) BMus (King's College London) Ikeshiro's research interrogates the materiality of sound through: Multichannel Ambisonics and directional audio Neural network-driven temporal dislocation Sonification of climate data and historical soundscapes Machine learning for artistic interpretation Interplay of identity and technology East Asian ideophonic traditions His 2010-2024 publications and installations reveal cross-disciplinary engagement with: Fractal mathematics in audiovisual art Algorithmic composition systems Interactive installation technologies Sonic cartography Historical memory in sound Collaborative research frameworks SoundLab, which he co-directs, develops spatial audio research at the intersection of: Technical innovation Cultural representation Experimental pedagogy Public engagement International artistic exchange Practice-based research

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.

Zhiyi Huangمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Algorithmic Game Theory
• Online Algorithms
• +۳ مورد دیگر

Zhiyi Huang is an Associate Professor of Computer Science at the University of Hong Kong, leading the Computer Science Division within the School of Computing and Data Science. He holds a PhD from the University of Pennsylvania (2013) and completed a postdoctoral fellowship at Stanford University (2013–2014). His research focuses on Theoretical Computer Science, Algorithmic Game Theory, Online Algorithms, and Differential Privacy, with notable contributions to Machine Learning and Computer Networks. Education: PhD in Computer and Information Science, University of Pennsylvania (2013) Postdoctoral Researcher, Stanford University (2013–2014) Bachelor's Degree from the Yao Class at Tsinghua University (2008) Research interests span foundational areas including algorithmic game theory, online optimization, and privacy-preserving mechanisms. He has pioneered work on revenue maximization in single-parameter settings and developed novel frameworks for analyzing price of anarchy in game theory. Key Awards: Early Career Award (Research Grant Council of Hong Kong, 2014) Best Paper Award at ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2015) Morris and Dorothy Rubinoff Dissertation Award (2013) Simons Graduate Fellowship in Theoretical Computer Science (2012–2013) Recent grants include studies on algorithmic foundations of Bayesian mechanism design (HK$675,647), online primal dual techniques (HK$496,028), and privacy-preserving mechanisms (HK$931,737). His work bridges theoretical advancements with practical applications in healthcare, autonomous systems, and cybersecurity. Notable Projects: Medical predictive systems for acute cardiopulmonary events AI-driven maritime navigation using AIS data Secure federated learning frameworks with blockchain

Xin Huangمشاهده پروفایل

دانشیار

• Graph Data Management
• Big Graph Mining & Visualization
• Social Network Analysis
• +۴ مورد دیگر

Xin Huang is an Associate Professor in the Department of Computer Science at Hong Kong Baptist University (HKBU), Faculty of Science. He serves as Coordinator of Research Postgraduate Programme (PhD&MPhil) and Coordinator of Programming Contest Teams. His educational background includes: Ph.D. in Systems Engineering and Engineering Management from The Chinese University of Hong Kong (2014) B.Eng. in Computer Science from Xiamen University (2010) Huang's research focuses on innovative technologies for large-scale graph data management and analysis. His work spans graph data management including keyword search and graph indexing, graph mining techniques for summarization and decomposition, community search algorithms, and graph learning approaches including graph neural networks. His research integrates theoretical foundations with practical applications in social network analysis and privacy-aware computing. His publication record shows consistent output in top-tier venues with a clear evolution from foundational graph algorithms to more complex applications involving dynamic and uncertain graphs, reflecting the growing importance of graph analytics in real-world systems. Notable awards include: Best Student Paper Award at ACM/IEEE IWLS 2023 Best Faculty Article Award from Chinese Communication Association (2022) HKBU President's Award for Outstanding Performance as Young Researcher (2021) RGC Early Career Award (2020) Best Paper Award at WISE 2019 Huang actively mentors PhD students and postdoctoral fellows, currently supervising five PhD candidates and four postdocs. His research has been supported by competitive grants including the RGC Early Career Award. He serves as Associate Editor for Data Science and Engineering and World Wide Web Journal, and participates extensively in program committees for major conferences including VLDB, ICDE, and WWW. As part of HKBU's Database Research Group, Huang contributes to a vibrant research environment that has secured over $10 million in research funding and published more than 200 papers in top venues.

Zihao Fuمشاهده پروفایل

دانشگاهی

• Large Language Models
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Zihao Fu is a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) . His work bridges computational methods with social sciences, focusing on model instability, repetition, hallucination, and algorithmic fairness. He has held research positions at the Oxford Internet Institute and the Language Technology Lab at the University of Cambridge. Education Ph.D. in Systems Engineering and Engineering Management (2017–2021), CUHK M.Eng. in Aeronautics and Astronautics (2012–2015), Beihang University B.Eng. in Automation Science (2008–2012), Beihang University His research explores the theoretical foundations of LLMs, addressing challenges like repetition , instability , and hallucination . He integrates linguistics , cognitive science , and fairness frameworks to enhance both foundational understanding and real-world applications of language technologies. Recent work includes biomedical NLP applications ( BAND dataset ), parameter-efficient model adaptation, and fairness toolkits ( OxonFair ). Zihao leads projects like BioCaster (disease outbreak monitoring) and CAM-Tool (cloud task distribution). He is actively mentoring postdoctoral researchers at CUHK and CUHK (Shenzhen), with expertise in machine learning , knowledge base integration , and parallel computing systems . His industry experience includes developing distributed algorithms at Alibaba Cloud’s PAI platform.

Xiaoyu Zhangمشاهده پروفایل

استادیار

• data visualization
• visual analytics
• human-computer interaction
• +۶ مورد دیگر

Xiaoyu Zhang is a tenure-track Assistant Professor at the School of Creative Media, City University of Hong Kong , where she conducts research at the intersection of computer science and art design. Her work focuses on integrating data visualization and artificial intelligence (particularly natural language processing ) for applications in education , smart manufacturing , and human well-being . She previously held a Postdoc Research Fellow position at the ETH AI Center , Zurich, and earned her Ph.D. in Computer Science from University of California, Davis under Prof. Kwan-Liu Ma, a Master’s from Zhejiang University, and a dual bachelor’s in Digital Media Art/Advertising from Xiamen University. Ph.D. in Computer Science, University of California, Davis M.Sc. in Computer Science, Zhejiang University B.Sc. in Digital Media Art, Xiamen University Her research bridges visual analytics , human-AI collaboration , and explainable AI through interdisciplinary methods. Key application domains include education technology, industrial AI, and health informatics. Recent publications (2021-2025) span venues like IEEE TVCG, IEEE VIS, ACM CHI, and ACL, with a 2022 Honorable Mention Best Paper Award at IEEE VIS. She has also secured multiple US patents and received recognition as UC Davis' Best Graduate Researcher in 2022. She has served as Associate Chair at ACM CHI (2025, 2026), organized the 6th Workshop on Visualization for AI Explainability at IEEE VIS 2023, and contributed to the AI House Davos 2024 committee. Industrial experience includes internships at Meta , Microsoft Research Asia , and Bosch Research . Her teaching portfolio spans courses in Information Visualization , Creative Coding , and Media Computing at CityU, ETH Zurich, and UC Davis.

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.

Sylvia Xihui Liuمشاهده پروفایل

دانشیار

• Design Management
• Design Policy
• Design-Driven Entrepreneurship
• +۶ مورد دیگر

Sylvia Xihui Liu is an Associate Professor at the School of Design, The Hong Kong Polytechnic University , where she has been employed since 2013. She serves as Assistant Dean (Academic Programmes) and Specialism Leader for MDes Innovative Business Design . Her industrial experience includes roles at NOVA Design, Zuki Design, and Golden Eagle Group. PhD in Design, The Hong Kong Polytechnic University MA in Design, Jiangnan University BE in Industrial Design, Nanjing University of Science & Technology Her research focuses on design policy , design management , and design-driven entrepreneurship , with significant contributions to China’s national innovation policies like the Made in China 2025 initiative. Recent work analyzes co-design methodologies in tourism and trust barriers in remote data collection. The Design Management Capability Framework , developed through her research, bridges design and business strategy. Her publications span design policy , creative industries , and intelligent systems for aging populations. School Research Excellence Award (2021) Annual Contribution Prize (2017) Second Prize of Industrial Design (2016) Top Ten Young Designers (2015) She has led funded projects including Made in China 2025 policy analysis and Design-Driven Entrepreneurship translational mechanisms. While specific student names are not listed, she supervises PhD and Master’s research in design and entrepreneurship.

Shiqi Wangمشاهده پروفایل

دانشیار

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

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

Chen Wangمشاهده پروفایل

استادیار

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

Chen Wang is an Assistant Professor in the Department of Statistics and Actuarial Science at The University of Hong Kong. He holds a PhD in Statistics from the National University of Singapore (NUS). His research focuses on Random Matrix Theory, Time Series Analysis, and High-dimensional Data Analysis. His work explores theoretical foundations and applications in econometrics, multivariate statistics, and high-dimensional inference. Key contributions include studies on spurious factor analysis, spectral distribution of time series, and cointegration analysis in large VARs. His teaching includes courses such as STAT2602 (Probability and Statistics II) and STAT3600 (Linear Statistical Analysis). Recent publications highlight advancements in AI-driven methodologies for single-cell biology, molecular modeling, and biomedical applications. Notable trends include integrating AI agents for experimental design, spatial biology analysis, and deep learning for medical imaging. Chen's work bridges statistical theory with practical applications, emphasizing high-dimensional data challenges in diverse scientific domains.