جستجوی استاد راهنمای دانشگاهی

• Condensed Matter Theory
• Quantum Simulation
• Topological Phases
• +۳ مورد دیگر

Prof. Yuxin Zhao (Department of Physics, Faculty of Science, The University of Hong Kong) is an Associate Professor specializing in the application of algebra representation and topology in condensed matter physics. He holds a B.Sc. from Peking University and a Ph.D. from HKU. B.Sc., Peking University (2006-2010) Ph.D., The University of Hong Kong (2010-2015) His research focuses on condensed matter theory and quantum simulation , particularly the interplay between topological phases , algebraic representation , and momentum-space symmetry . He has published extensively on topics such as non-Hermitian systems , projective symmetry algebra , and spacetime crystals . Recent publications highlight trends in topological semimetals , non-Abelian braiding , and symmetry-enriched topological charges . His work bridges theoretical physics with quantum information and materials science . Distinguished Young Scholars, Jiangsu Province, China (2021) 1000-Talent Program for Young Scientists (2016) Prof. Zhao actively supervises PhD students including Wang Xiang, Wang Peiyuan, Wang Aoning, Lyu Junkun, and Liu Tianrun. He leads the 2024 grant Exploring novel topological phases protected by momentum-space nonsymmorphic symmetries (HK$910,742) and co-investigated the 2017 project Crystalline Gapless and Gapped Topological Phases (HK$472,351). He serves as Council Member of the Physical Society of Hong Kong (2023-2024).

Hailiang Chenمشاهده پروفایل

استاد

• Artificial Intelligence
• FinTech
• Social Media
• +۸ مورد دیگر

Hailiang Chen serves as Professor in Innovation and Information Management, Assistant Dean (Taught Postgraduate), and Director of the Artificial Intelligence Research Institute at HKU Business School, The University of Hong Kong. His academic journey includes a PhD and MS from Purdue University and a BM from Tsinghua University. Doctoral Degree: Management Information Systems, Purdue University Master Degree: Economics, Purdue University Bachelor Degree: Information Management and Information Systems, Tsinghua University Professor Chen's research spans artificial intelligence, FinTech, social media analytics, and platform economics, with significant contributions to understanding how digital interactions shape financial markets and consumer behavior. His work frequently examines the intersection of technology adoption and economic outcomes, particularly in cryptocurrency markets, live-stream commerce, and venture capital decision-making. His research methodology combines large-scale data analysis with experimental designs to uncover causal relationships in digital ecosystems. His publications in elite journals like Journal of Financial Economics and Management Science demonstrate consistent impact, with multiple ESI Highly Cited Papers. Current projects include Gov-RAG for e-government services and comparative studies of AI search tools. His research has received continuous funding from Hong Kong's Research Grants Council for five consecutive years (2019-2023). Faculty Outstanding Researcher Award, HKU Business School (2022-23) INFORMS ISS Sandra A. Slaughter Early Career Award (2022) Association for Information Systems Early Career Award (2019) Three ESI Highly Cited Papers (Top 1% in field) Professor Chen actively contributes to academic service as Associate Editor for Journal of Management Information Systems and MIS Quarterly , and serves as Program Chair for the International Conference on Smart Finance. His industry collaborations include Alibaba, HSBC, and China Construction Bank, bridging academic research with real-world business applications in AI implementation and digital transformation.

Rynson W.H. Lauمشاهده پروفایل

استاد

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

Oscar Carl Olof Dahlstenمشاهده پروفایل

دانشیار

• Quantum Information Science
• Information Thermodynamics
• Foundations of Quantum Theory
• +۳ مورد دیگر

Oscar Carl Olof Dahlsten is an Associate Professor in the Department of Physics at City University of Hong Kong. He works in the field of quantum information science with research spanning information thermodynamics, foundations of quantum theory, and quantum computation and machine learning. His academic journey includes training at Imperial College and previous positions at ETH Zurich, NUS Singapore, Oxford University, and SUSTech before joining CityUHK. Dahlsten's research interests focus on the intersection of quantum mechanics and information theory. His work explores how quantum systems process information, the thermodynamic implications of quantum operations, and the application of quantum principles to computational problems. Key areas include quantum causal inference, quantum energy harvesting, black hole information theory, and quantum machine learning algorithms. His fingerprint analysis shows strong contributions to Quantum Theory (100%), Statistical Mechanics (55%), Quantum Dot physics (55%), and Free Energy concepts (40%). Recent publications demonstrate a strong trend toward experimental validation of quantum information concepts, particularly in quantum causal inference and quantum thermodynamics. His work bridges theoretical foundations with practical applications, especially in energy harvesting and quantum computing. The integration of quantum principles with thermodynamic laws appears as a consistent theme across his recent publications. Dahlsten currently serves as Principal Investigator for the GRF project 'Exploiting Quantum Systems for More Efficient Extraction of Energy From Random Sources' starting September 1, 2025. He actively supervises PhD students in quantum information science and is accepting new PhD candidates. His research group focuses on cutting-edge problems at the intersection of quantum information, thermodynamics, and computation.

• Simulation
• Computational Probability
• Queueing Theory
• +۲ مورد دیگر

Peter W. Glynn is the Thomas Ford Professor in the Department of Management Science and Engineering (MS&E) at Stanford University's School of Engineering, and also holds a courtesy appointment in the Department of Electrical Engineering. Additionally, he serves as a Senior Fellow of the Hong Kong Institute for Advanced Study at City University of Hong Kong. His distinguished career spans over four decades, with significant contributions to the fields of simulation, computational probability, and stochastic modeling. Professor Glynn received his Ph.D. in Operations Research from Stanford University in 1982 and his B.S. with Honors in Mathematics from Carleton University in 1978. His academic journey began at the University of Wisconsin at Madison (1982-1987) before returning to Stanford, where he has held various leadership positions including Deputy Chair of MS&E (1999-2005), Director of Stanford's Institute for Computational and Mathematical Engineering (2006-2010), and Chair of MS&E (2011-2015). His research interests focus on simulation , computational probability , queueing theory , statistical inference for stochastic processes , and stochastic modeling . Professor Glynn's work has developed algorithms widely used across the field of Monte Carlo simulation, with applications in financial risk management, service systems engineering, logistics, and retail operations. His recent publications demonstrate continued innovation in areas such as numerical methods for stochastic systems, rare-event simulation, and analysis of queueing systems under various traffic conditions, showing a strong trajectory of advancing both theoretical foundations and practical applications. Professor Glynn's scholarly contributions have been recognized with numerous prestigious awards, including: Fellow of INFORMS (2007) Fellow of the Institute of Mathematical Statistics (1998) John von Neumann Theory Prize from INFORMS (2010) Member of the US National Academy of Engineering (2012) Lifetime Professional Achievement Award, INFORMS Simulation Society (2021) Philip McCord Morse Lecturer, INFORMS (2020) Throughout his career, Professor Glynn has mentored numerous doctoral students whose research has made significant contributions to operations research and related fields. His editorial service has been extensive, including founding Editor-in-Chief of Stochastic Systems and service on the editorial boards of leading journals in operations research, probability, and statistics. His professional service extends to numerous advisory boards and committees at national and international levels, reflecting his standing as a leader in his field.

• Optical Physics
• Nanophotonics
• Light-Matter Interaction
• +۵ مورد دیگر

Yi Yang serves as an Assistant Professor in the Department of Physics at The University of Hong Kong (HKU), Faculty of Science, joining the institution in 2022 as an HKU-100 Scholar. His academic journey includes foundational training at Peking University and advanced research at MIT. Education: Bachelor of Science (B.Sc.), Peking University Master of Science (M.Sc.), Peking University Doctor of Philosophy (Ph.D.), Massachusetts Institute of Technology (MIT) Professor Yang's research centers on optical physics and nanophotonics , specifically exploring light-matter interactions with free electrons and synthetic gauge fields. His pioneering work in non-Abelian physics bridges photonic and acoustic systems, while his investigations into free-electron radiation and topological photonics drive innovations in nanoscale electromagnetism. These efforts yield fundamental insights with applications in quantum simulation, novel light sources, and advanced materials engineering. Recent publications (2023-2024) reveal a pronounced focus on non-Abelian phenomena and synthetic gauge fields , evidenced by high-impact papers in Science and Nature . His work consistently integrates theoretical frameworks with experimental validation, establishing new paradigms in photonic flatband resonances and non-Hermitian systems. Scientific Awards: HKU-100 Scholar Professor Yang actively contributes to HKU's research ecosystem through graduate supervision and collaborative projects. While specific grant details aren't public, his publication trajectory indicates substantial research funding supporting his investigations into quantum photonics and nanoscale light-matter interactions. His laboratory operates within HKU's Department of Physics, leveraging specialized facilities in the Chong Yuet Ming Physics Building for experimental nanophotonics research and theoretical modeling of complex optical systems.

• Quantum Many-Body Physics
• Ultracold Atomic and Molecular Physics
• Quantum Simulation
• +۳ مورد دیگر

Assistant Professor Zhendong Zhang is affiliated with the Department of Physics at the Faculty of Science, The University of Hong Kong. He received a B.S. in physics from Huazhong University of Science and Technology and a Ph.D. from the University of Chicago under Prof. Cheng Chin. His research focuses on quantum many-body physics and ultracold chemical reactions, utilizing advanced experimental techniques in ultracold atomic systems. B.S., Huazhong University of Science and Technology Ph.D., University of Chicago Zhang’s work explores the intersection of quantum optics, synthetic gauge fields, and quantum simulation. His recent publications highlight experiments on magnetic quantum gases , optical cavity coupling , and non-equilibrium dynamics in Bose-Einstein condensates, with implications for understanding fundamental quantum phenomena and chemical processes in degenerate systems. His selected publications reveal a focus on quantum many-body systems , ultracold atomic physics , and quantum simulation , progressing from foundational studies on atomic-to-molecular condensate transitions (2021) to groundbreaking work on Unruh radiation analogs (2019) and domain-wall dynamics (2022). Collaborations with leading researchers like Cheng Chin and Benjamin Lev underscore cross-institutional impact. Outstanding Dissertation Award, International Organization of Chinese Physicists and Astronomers (OCPA) Zhang’s postdoctoral work at Stanford as a Bloch Fellow involved constructing high-finesse multimode optical cavity experiments for magnetic quantum gases. His current research at HKU continues to push boundaries in ultracold ion trapping and quantum degenerate gas interactions.

Yan Tina Luximonمشاهده پروفایل

استاد

• Ergonomic design
• Anthropometry
• 3D digital human modeling
• +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).

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

• Astrophysics
• Galaxy Formation
• Stellar Population Synthesis
• +۳ مورد دیگر

Meng Gu is an Assistant Professor in the Department of Physics at The University of Hong Kong, where she conducts research on galaxy formation and stellar population synthesis. She holds the prestigious HKU-100 Scholar position and specializes in understanding the physical mechanisms driving the interplay between star formation and galaxy mass assembly. Education: Bachelor of Science (BSc) from Nanjing University (NJU) Master of Arts (MA) from Harvard University PhD from Harvard University, completed with Prof. Charlie Conroy Prof. Gu's research addresses fundamental questions in astrophysics regarding the stellar initial mass function of galaxies, its global and local variations, and implications for mass measurements. She investigates how environmental factors shape galaxy formation and evolution, particularly focusing on how massive galaxies grow and what spatial information of stellar populations reveals about these processes. Her work combines observational data with advanced modeling techniques to unravel the complex history of galaxy assembly. Analysis of Prof. Gu's publications reveals a consistent focus on massive galaxy evolution, with particular emphasis on the stellar initial mass function, galaxy cluster dynamics, and ultra-diffuse galaxies. Her research spans observational astronomy using major telescope facilities, theoretical modeling, and computational cosmology. The progression of her work shows increasing sophistication in connecting observational data with theoretical frameworks to understand galaxy formation mechanisms. Scientific Awards: HKU-100 Scholar Henry Norris Russell postdoctoral fellow at Princeton University Prof. Gu has secured research funding to utilize major observational facilities including Magellan Telescopes, ESO's Very Large Telescope, and the Sloan Digital Sky Surveys. She is preparing to leverage next-generation facilities like the James Webb Space Telescope (JWST) and Subaru Prime Focus Spectrograph (PFS) survey for future research. Her collaborative work spans multiple international institutions, reflecting the global nature of modern astrophysics research. Prof. Gu is actively involved in observational astronomy projects and collaborates with major research groups working on galaxy evolution. Her work with the MASSIVE survey represents a significant contribution to understanding the most massive galaxies in the nearby universe, utilizing high-quality spectroscopic data to constrain fundamental properties of stellar populations.

Johan F. Hoornمشاهده پروفایل

استاد

• Social Robotics
• Computational Creativity
• AI and Design
• +۵ مورد دیگر

Johan F. Hoorn is an Interfaculty Full Professor at The Hong Kong Polytechnic University, jointly affiliated with the School of Design and the Department of Computing. He is also the Associate Director of PolyU Academy for Interdisciplinary Research and Research Institute for Quantum Technology. PhD in General Literature and Computer Science Recipient of multiple national and international awards Active in RGC Theme-based Research Scheme (2025-2029) Research interests span social robotics, affective computing, quantum cognition, and the observer effect. His work focuses on integrating AI with human psychology to address mental health challenges and enhance creativity. Recent articles highlight trends in human-robot empathy, quantum probability applications, and AI-assisted artistic innovation. Key subfields include emotional bonding, media inequality, real-time cinematic design, and moral reasoning in robots. Scientific awards include the Huibregtsen Prize (2020), Eureka Award (2015), and Pilot Science Appreciated Award (2021). He was also recognized with a Burgen Scholarship (2001) and Lorentz Fellowship (2010-2011). He leads projects like Negative-mood reduction among HK youth with robot PAL (HK$3M grant) and SELEMCA (M€4.6 grant). His work has been exhibited at leading museums, including the Victoria & Albert Museum (2024).

Can Liuمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Spatial Computing
• +۵ مورد دیگر

Dr. Can Liu is an Assistant Professor at the School of Creative Media, City University of Hong Kong, where she leads the ERFI Lab (Laboratory of Empirical Research for Future Interfaces). Her research focuses on designing future interfaces for ubiquitous technologies through empirical understanding of human cognition and behavior, with emphasis on multimodal interaction combining physical and digital elements. Education: PhD in Human-Computer Interaction, Université Paris-Sud (France), INRIA labs ex)situ and ILDA MSc in Media Informatics, RWTH Aachen University (Germany) Dr. Liu's research spans three primary domains: AI-assisted Input (using LLMs/NLP to enhance text manipulation and speech interfaces), Spatial Computing (multimodal interfaces for AR/VR and large displays), and Hybrid/Remote Collaboration (supporting intuitive remote interaction through understanding collocated collaboration). Her work integrates empirical user studies with real-world system deployments in public spaces. Recent publications demonstrate strong trends toward LLM-integrated interfaces, wearable computing applications, and novel interaction techniques for foldable devices. Her team consistently publishes at top venues including CHI, UIST, and CSCW, with increasing focus on practical AI integration for everyday tasks. Awards and Recognition: Best Paper Award at ACM CHI 2014 (top 1%) Honourable Mention at ACM CHI 2012 (top 5%) Dr. Liu actively mentors PhD students and researchers while securing substantial research funding including Google Faculty Research Awards, National Natural Science Foundation grants, and RGC Early Career Schemes. She serves on numerous program committees including ACM CHI (Associate Chair 2024, 2022, 2021, 2020, 2019, 2017) and co-organizes research initiatives like the HCIX Summer Research Program. Her laboratory ecosystem includes the ERFI Lab, affiliation with the Augmented Materiality Lab and Kowloon Interaction Center, and active participation in the Greater Bay HCI community, supporting both fundamental research and industry collaboration with partners including Google, Huawei, and Lenovo.

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.

• Computational Physics
• Statistical Physics
• Complex Systems
• +۲ مورد دیگر

Dr. Judy Fung Kiu Chow serves as an Assistant Lecturer in the Department of Physics within the Faculty of Science at The University of Hong Kong. She has extensive experience teaching undergraduate courses including Computational Physics, Introductory Physics, Mathematical Methods of Physics, and Quantum Physics for many years, actively encouraging student engagement on academic and personal development matters. Her academic foundation was built entirely at HKU: Bachelor of Science (B.Sc.) in Physics Master of Philosophy (M.Phil.) in Physics Doctor of Philosophy (Ph.D.) in Physics Research expertise centers on Complex Systems and Econophysics , with pioneering work on the Minority Game model to analyze strategic decision-making in competitive environments. Her methodology integrates statistical mechanics and agent-based simulations to decode collective behavior in financial markets, wealth distribution patterns, and adaptive system dynamics. Publication trends from 2002-2008 reveal sustained innovation in minority game theory, exploring peer pressure effects, multi-choice scenarios, memory mechanisms, and profit optimization strategies. These contributions bridge physics principles with socio-economic modeling, particularly through collaborations with H.F. Chau across nine significant papers in journals like Physical Review E and Physica A .

Nan Chenمشاهده پروفایل

استاد

• Financial Engineering
• FinTech
• Quantitative Finance
• +۷ مورد دیگر

Prof. Nan Chen is a Professor in the Department of Systems Engineering and Engineering Management at The Chinese University of Hong Kong (CUHK). He holds a PhD from Columbia University (2006) and directs the Bachelor of Engineering in Financial Technology (FinTech) and the Master of Science in Financial Engineering at CUHK-Shenzhen. His research focuses on quantitative finance, systemic risk, Monte Carlo simulation, and reinforcement learning. He has authored over 40 papers in top journals like Operations Research and Review of Financial Studies . Education : BSc and MSc in Probability & Statistics, Peking University (1998–2001) MPhil/PhD in Operations Research, Columbia University (2005–2006) Research Interests : FinTech and quantitative finance Systemic risk modeling and network analysis Reinforcement learning and stochastic control Monte Carlo methods and computational finance Awards & Grants : Best Student Paper Award, INFORMS (2006) Exemplary Teaching Awards (2009, 2017) Over HK$7M in GRF grants (2008–2023) Second Prize, Jiangsu Province Social Science Award (2023) Public Service : Member of Hong Kong's Payment Systems Tribunal and Insurance Appeals Tribunal, and reviewer for major journals like Mathematical Finance and Operations Research . Key Contributions : Pioneered Ito-Taylor expansions for diffusion models, dual methods for stochastic control, and liquidity risk frameworks. Led development of Hong Kong's first FinTech undergraduate program.