جستجوی استاد راهنمای دانشگاهی

Prof. Hayden Kwok Hay SO is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Electrical and Electronic Engineering. He currently serves as Acting Director of the School of Innovation and previously co-directed the Computer Engineering Program. His research focuses on reconfigurable computing systems, FPGA-based architectures, and their applications in AIoT, medical imaging, and high-performance computing. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (1998–2007). Prof. So has been recognized with awards such as the IEEE-HKN Teaching Award (2021), Croucher Innovation Award (2013), and multiple teaching excellence awards. He leads the Computer Architecture & System Research Lab (CASR) and co-founded the Joint Lab on Future Cities (JLFC). His work spans FPGA overlay architectures, graph processing systems, and hardware-software co-design for efficient computing. Key research contributions include advancements in FPGA-based reconfigurable systems, sparse dataflow architectures, and medical imaging accelerators. He has secured grants for projects like 'Advanced machine vision guided aquatic surface vehicles' and 'Efficient and Productive Parallel Data Processing in Hybrid FPGA-CPU Clusters.' Prof. So has advised numerous students and researchers, contributing to over 150 peer-reviewed publications. His current projects explore AI hardware acceleration, neuromorphic computing, and FPGA-driven solutions for big data challenges.

• Reconfigurable Computing
• FPGA-Based Systems
• Computer Architecture
• +۷ مورد دیگر

Dr. Lingpeng Kong is an Assistant Professor in the Department of Computer Science at the University of Hong Kong (HKU), affiliated with the School of Computing and Data Science. He obtained his PhD from Carnegie Mellon University in 2017, co-advised by Noah Smith and Chris Dyer. Previously, he was a research scientist at Google DeepMind (2017–2020). His research focuses on natural language processing (NLP), machine learning, and deep learning, particularly in structured prediction and representation learning. He co-directs the HKU NLP Lab. Notable contributions include work on syntactic parsing, neural architecture design, and lifelong learning. He has received an Outstanding Paper Award at EACL 2017. Dr. Kong teaches courses such as Natural Language Processing (COMP3361/COMP7607) and Machine Learning (COMP3314), and has advised multiple research projects at HKU.

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Sky Lo Tian Tian is an Assistant Professor at the School of Design, Hong Kong Polytechnic University. His research focuses on "Spatial Phygital Interaction", integrating technologies like XR (Extended Reality), BIM (Building Information Modeling), and gamification to bridge virtual and physical environments through human-centred architectural design. Key expertise includes computational architecture, digital fabrication, and interactive design Developed novel concepts like Human-Virtual Reality Interaction (HVRI) and phygital-aided construction systems His notable projects include the Green Weaved Corridor bamboo pavilion in Chaozhou, China, and the Meta Archive platform for 3D model archiving. He actively organizes workshops at international venues like DigitalFuture, CCD-ASC, and POLAR. Scientific Awards : Full Doctoral Scholarship recipient from The Chinese University of Hong Kong and Victoria University of Wellington

• Computational Architecture
• Building Information Modeling (BIM)
• Gamification Application
• +۱۱ مورد دیگر

Dr. Yingyu Liang is an Associate Professor at the University of Hong Kong (HKU), affiliated with the Department of Computer Science and the Musketeers Foundation Institute of Data Science. Previously, he held an Associate Professor position at the University of Wisconsin-Madison and was a postdoc at Princeton University. He earned his PhD from Georgia Tech and holds M.S. and B.S. degrees from Tsinghua University. His research focuses on theoretical foundations of machine learning, particularly optimization and generalization in deep learning, robust machine learning, and practical applications. Key contributions include analyzing neural network feature learning, adversarial robustness, and contrastive learning efficiency. Education: PhD (Georgia Tech, 2014), M.S. (Tsinghua, 2010), B.S. (Tsinghua, 2008) Awards: NSF CAREER Award Labs/Groups: Research Group focused on theoretical ML and algorithm design Publications span top venues like NeurIPS, ICML, and ICLR, addressing topics such as deep learning theory, adversarial robustness, and graph representation learning.

• Machine Learning
• Optimization in Deep Learning
• Generalization in Neural Networks
• +۳ مورد دیگر

Professor Benjamin C.M. Kao is a faculty member in the Department of Computer Science at The University of Hong Kong (HKU), affiliated with the School of Computing and Data Science. He holds a BSc from HKU (1989) and a PhD from Princeton University (1995). His career includes roles as a teaching/research assistant at Princeton (1989-1991) and a research fellow at Stanford University (1992-1995). His research focuses on Database Management Systems, Data Mining, Real-time Systems, and Information Retrieval Systems. Notable contributions include S-OLAP for sequence data analysis, collaborative resource discovery in social tagging systems, and algorithms for mining periodic patterns in sequences. He has led research grants such as the GRF-funded 'Online Analytical Processing on Sequence Data' (2008) and computational studies in uncertain data mining (2006). Professor Kao has served on program committees for major computer science conferences and reviewed for leading journals. His work bridges theoretical foundations with practical applications in data systems and information retrieval.

• Database Management Systems
• Data Mining
• Real-time Systems
• +۱ 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.

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

Dr. Difan Zou is an Assistant Professor in the Department of Computer Science at the University of Hong Kong's School of Computing and Data Science. He holds a PhD in Computer Science from UCLA and degrees in Applied Physics and Electrical Engineering from the University of Science and Technology of China (USTC). His research focuses on machine learning theory, optimization, and learning structured data such as time-series and graph data, with an emphasis on understanding deep learning's theoretical underpinnings like optimization trajectories and generalization properties. Dr. Zou's academic background includes a B.S. from USTC's School of Gifted Young (Applied Physics) and a M.S. in Electrical Engineering from the same institution. His work bridges theoretical foundations and practical applications, addressing challenges in adversarial robustness, algorithm design for deep neural networks, and explainable machine learning systems in healthcare and finance. His research projects aim to establish rigorous frameworks for deep learning optimization, develop efficient training algorithms, and integrate conventional statistical models with machine learning for improved interpretability. He has received the Bloomberg Data Science Ph.D. Fellowship and has contributed to top-tier conferences like ICML, NeurIPS, and ICLR.

• Machine Learning Theory
• Deep Learning Theory
• Optimization Algorithms
• +۵ مورد دیگر

Rynson W.H. Lau is a Professor of Computer Science at City University of Hong Kong (CityU), leading research in Computer Graphics, Computer Vision, and Deep Learning. He holds an Honorary Professorship at Swansea University. Previously, he served on faculties at Durham University and The Hong Kong Polytechnic University. His work focuses on advancing graphics and vision techniques, including deep learning applications for graphics/vision problems, with publications in top venues like SIGGRAPH, CVPR, and NeurIPS. He has received the Adobe Research Gift (2023) and the Springer Nature Editorial Contribution Award (2025) for his editorial contributions to the International Journal of Computer Vision . Education: B.Sc. (First-class Honors) in Computer Systems Engineering from University of Kent Ph.D. in Computer Science from University of Cambridge Research Interests: Computer Graphics: Focused on 3D reconstruction, rendering, and real-time performance capture. Computer Vision: Specializing in saliency detection, object recognition, and low-light scene enhancement. Deep Learning: Developing generative models and diffusion-based frameworks for graphics and vision tasks. Editorial Roles: Editorial Board Member, International Journal of Computer Vision and IET Computer Vision . Guest Editor for special issues in journals like ACM Transactions on Internet Technology and IEEE Transactions on Multimedia. Teaching: 2024/25 Academic Year: CS4185: Multimedia Technologies and Applications CS4188/CS5188: Virtual Reality Technologies and Applications Research Team: Advises over 20+ students and collaborates internationally. Recent projects include AI-driven VR systems for healthcare and advanced 3D content generation using diffusion models.

• Computer Graphics
• Computer Vision
• Deep Learning
• +۳ 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.

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

Jeffrey C. F. Ho is an Associate Professor at the School of Design, The Hong Kong Polytechnic University. He serves as Deputy Specialism Leader of Interaction Design and Chairman of the School Learning & Teaching Committee. His research centers on virtual reality (VR) and interaction design, applying social science principles to influence attitudes and behaviors through immersive technologies. He leads projects in VR applications for safety training, virtual museums, and healthcare, and collaborates with the Asian Lifestyle Design Lab and the Technology and Social Behavior Lab at the University of Illinois at Urbana-Champaign. PhD in Communication, City University of Hong Kong MSc in Human-Computer Interaction with Ergonomics, University College London MPhil in Computer Science, The University of Hong Kong BEng in Software Engineering, The University of Hong Kong Ho’s research explores VR’s role in perspective-taking experiences, focusing on empathy, prosocial behavior, and spatial cognition. His work bridges VR with public health, education, and cultural preservation, such as designing VR environments for elderly care and dietary reflection. His recent publications highlight trends in generative AI ethics, beginner-friendly design software, and spatio-social impacts in VR applications. His articles span virtual reality games, VR safety training, and interactive museum design, with keywords like Virtual Reality, Human-Computer Interaction, and Cultural Preservation. Key subfields include immersive technology, social behavior analysis, and ethical design frameworks. UGC Teaching Award - Nominee (2024) Best Paper Award, EAI ArtsIT 2020 (2020) Exemplary Teaching and Learning Award - Merit (2024) QS Reimagine Education Awards 2024 - Global Education Award (2024) QS Reimagine Education Awards 2024 - Gold Award in Smart Omnichannel Campus (2024) Ho has secured grants from Hong Kong’s Research Grant Council, including HK$678,607 for immersive VR construction safety training (2024–2026) and HK$741,961 for VR safety education focusing on accident victims (2021–2023). He contributes as a reviewer for journals like Universal Access in the Information Society and Frontiers in Psychology , and leads teaching initiatives in information architecture and interactive media design.

• Virtual Reality
• Interaction Design
• Human-Computer Interaction
• +۶ مورد دیگر

Prof. Yan Tina Luximon is a Full Professor and Associate Dean (Research) at the School of Design, The Hong Kong Polytechnic University. She chairs the School Research Committee, leads the Asian Ergonomics Design Lab, and serves as Deputy Discipline Leader for BA (Product Design). Her work bridges ergonomics, AI design tools, and 3D human modeling in cross-cultural contexts. Education: PhD in Ergonomics from The Hong Kong University of Science and Technology Research interests span Ergonomics in product design 3D digital human modeling for AI applications Anthropometry and cultural design differences Statistical modeling for head/face product development Human-computer interaction and AI visualization Recent publications focus on AI-enhanced 3D head modeling, ergonomic healthtech products, and cross-cultural design psychology, with applications in robotics, mobile technology, and medical devices. Scientific awards include: Gold Medal with jury congratulations at Geneva Inventions 2024 Silver Award at IDEA 2023 for adaptive eyewear design Best Innovation Award at ACED Japan 2017 She supervises postgraduate research and leads projects funded by the General Research Fund (RGC GRF) and Laboratory for AI in Design, including AI Powered Ergonomic Product Design (2025) and 4D Head Movement Prediction (2024).

• Ergonomic design
• Anthropometry
• 3D digital human modeling
• +۶ 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

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

Dan Wang is a Professor in the Department of Computing at The Hong Kong Polytechnic University. He holds a B.Sc. from Peking University, M.Sc. from Case Western Reserve University, and Ph.D. from Simon Fraser University, all in Computer Science. Expertise: Network Architecture, QoS, Smart Building, Big Data, Industry 4.0 Awarded ACM Distinguished Scientist 2023 for contributions to cyber-physical energy systems Recipient of Best Paper Awards at ACM Buildsys (2018), ACM e-Energy (2018), and multiple conference recognitions Research focuses on smart building energy systems, edge computing, and applied AI in industry. Active in organizing conferences like ACM Buildsys 2024 (TPC Co-Chair) and ACM e-Energy 2022 (General Co-Chair). Advises 5-7 students annually, with current Ph.D. candidates and postdocs working on edge computing and AI applications. Former students hold roles at Tencent, Huawei, and JD.com.

• Network Architecture
• Quality-of-Service (QoS)
• Smart Building
• +۵ 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.

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

Professor Shenghua Gao is an Associate Professor at the School of Computing and Data Science of the University of Hong Kong (HKU), concurrently serving as Assistant Director for Shanghai Initiatives. He holds a PhD from Nanyang Technological University. His research focuses on integrating machine learning, spatio-temporal data analysis, and database systems to address challenges in mobility prediction, traffic management, and geospatial representation learning. He has contributed significantly to trajectory modeling, indexing frameworks for multi-dimensional data, and the application of large language models (LLMs) in spatio-temporal contexts. Key research interests include: Spatio-Temporal Data Science: Developing frameworks for efficient processing and analysis of point cloud, trajectory, and traffic data. Machine Learning for Databases: Innovating indexing algorithms (e.g., BMTree, MAST) and query optimization techniques leveraging ML. Trajectory and Mobility Prediction: Creating personalized models for next-location prediction and transfer learning across regions. Geographic AI (GeoAI): Enhancing road network representation and urban function inference using physics-guided and foundation models. Recent work highlights include the ST-LLM+ framework for traffic prediction, the MAST system for point cloud analytics, and the exploration of City Foundation Models for urban challenges. His publications span top venues in databases (SIGMOD, VLDB) and AI/data science (ICML, NeurIPS). While no awards are explicitly mentioned, his prolific output and leadership roles indicate significant academic contributions. He is actively involved in teaching and supervising research in the School’s undergraduate and postgraduate programs, including MSc(AI) and MPhil/PhD tracks.

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