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Ravishankar RamanathanView profile

Assistant Professor

• Quantum Cryptography
• Quantum Information Theory
• Device-Independent Quantum Information Processing
• +3 more

Ravishankar Ramanathan is an Assistant Professor at the University of Hong Kong's School of Computing and Data Science, Department of Computer Science. His research spans Quantum Cryptography, Quantum Information Theory, and Human-Robot Interaction. He holds a PhD from the National University of Singapore (2013), with prior postdoctoral roles at The National Quantum Information Centre (Poland), Université Libre de Bruxelles, and the University of Oxford. His work includes foundational studies in quantum mechanics and advanced robotics applications, with over 30 refereed publications in top journals like Nature Communications and Physical Review Letters. Research interests focus on quantum device-independent protocols, randomness amplification, and human-centric robotics systems. His lab (QIFT Group: https://qift.weebly.com/) explores both theoretical quantum mechanics and practical robotics solutions for mobility assistance and social interaction. Recent publications highlight contributions to quantum cryptography (e.g., noise-tolerant protocols) and autonomous systems (e.g., robotic wheelchair navigation and social robot design). He collaborates internationally, bridging quantum theory with real-world robotics applications.

Clifford Sze Tsan ChoyView profile

Senior Lecturer

• Interaction design
• Physical computing
• Digital fabrication
• +4 more

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.

Normann WitzlebView profile

Associate Professor

• Privacy Law
• Data Protection Law
• Torts
• +4 more

Normann Witzleb is an Associate Professor at the Faculty of Law of The Chinese University of Hong Kong , joining in 2021. He previously served as Associate Professor and Associate Dean (International and Engagement) at Monash University and maintains an adjunct position there. Education Dr. iur., European University Viadrina Frankfurt/O Germany LLB, Murdoch University Second German State Law Exam, Kammergericht Berlin First German State Law Exam, Bavaria Research Interests Privacy and data protection law Torts and remedies Comparative legal analysis Digital governance and surveillance Scientific Awards and Grants Meta XR Programs & Research Fund (2023) Hong Kong University Grants Committee (2022) German Academic Exchange Service Joint Research Scheme (2021) Monash Teaching Excellence Award (2010) Advising and Funding Prof. Witzleb supervises PhD students in privacy law, torts, and comparative law. His funded projects include collaborations with the Australian Attorney-General’s Department and Office of the Australian Information Commissioner , focusing on data governance and AI regulation. Labs and Teams He contributes to the Obligations Lab Asia and participates in global conferences on digital law, including the Metaverse Law Conference and EU external trade data protection workshops .

• Algorithms
• Combinatorial Optimization
• Discrete Metric Spaces
• +7 more

Hubert Tsz-Hong Chan is an Associate Professor in the Department of Computer Science, School of Computing and Data Science at The University of Hong Kong. He earned his PhD in 2007 from Carnegie Mellon University under the supervision of Anupam Gupta, followed by post-doctoral research at the Max-Planck-Institut für Informatik (2007-2009). Education PhD in Computer Science, Carnegie Mellon University, 2007 Research Interests Dr Chan's research lies at the intersection of algorithms , combinatorial optimisation , discrete metric spaces , and security & privacy . A recurring theme is the design of provably efficient approximation algorithms for geometric and graph-theoretic problems under realistic or adversarial settings. Representative contributions include polynomial-time approximation schemes (PTAS) for TSP and Steiner Forest in doubling metrics, spectral analysis of hypergraph Laplacians, and foundational work on differential obliviousness and oblivious RAM. Publications & Trends With more than 80 peer-reviewed papers in premier venues such as JACM , SIAM Journal on Computing , Algorithmica , FOCS , SODA , EUROCRYPT , ASIACRYPT , CCS , and WWW , his recent output (2018-2021) demonstrates a shift toward privacy-preserving algorithms, differential obliviousness, and socially-aware optimisation models, often combining rigorous theory with practical datasets like Netflix and Twitter. Scientific Awards IPDPS 2019 Best Paper Award WWW 2018 Honorable Mention Students & Mentoring Dr Chan has successfully graduated 17 PhD and MPhil students and currently mentors 7 PhD candidates and 1 MPhil student. His graduates have secured academic and industry positions worldwide, and their theses frequently build on his funded projects. Research Funding & Labs Since 2012 he has been Principal Investigator on 12 competitive grants from the Hong Kong Research Grants Council (RGC), totalling more than HK$8 million, spanning topics from privacy-preserving aggregation to Byzantine-resilient federated learning. While no dedicated laboratory name is advertised, his group operates within the Security & Privacy and Algorithms Labs in the Department of Computer Science.

• Computer Graphics
• 3D Computer Vision
• User Interaction
• +5 more

Chi-Wing FU, Philip is a Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK). He holds dual roles in research and education, including Associate Editor-in-Chief of IEEE Computer Graphics and Applications. His research focuses on computer graphics, 3D vision, and human-computer interaction, with over 100 publications in top venues like SIGGRAPH, CVPR, and IEEE Visualization. Education: B.Sc. (1st Hons), Computer Science & Engineering, CUHK M.Phil., Computer Science & Engineering, CUHK PhD, Indiana University, Bloomington Research Interests: Dr. Fu's work spans 3D shape generation, computational LEGO design, AR visualization, and robotic interaction. He has pioneered projects like Make-A-Shape (large-scale 3D modeling) and DreamStone (text-driven 3D creation). His team also develops tools for medical data visualization and hand-object pose estimation. Recent Trends in Articles: Recent work emphasizes AI-driven creativity (e.g., LEGO art, text-to-3D systems) and real-time AR applications. His publications often bridge theory (e.g., generative models) with practical systems (e.g., user interfaces for design). Awards: Postgraduate Research Output Award (2023) MSRA Fellowship Nomination (2022) Best Associate Editor (IEEE CG&A) Outstanding Reviewer (ICCV 2021, CCF CAD/CG 2023) Advising & Grants: Supervised over 40 PhD/Master students and postdocs. Active in securing grants for projects like computational LEGO design (with Autodesk), medical AR visualization, and 3D generative AI. Collaborates with industry partners like Adobe and Huawei. Labs & Teams: Leads the Computational Design and Visualization Lab, focusing on 3D systems, robotics, and creative AI. Key projects include the LEGO Sketch Art toolchain and the HandShadowPoser AR system.

Kai Ming LeeView profile

Lecturer

• Quantum Field Theories
• Leaky Systems
• Mathematical Physics
• +3 more

Dr. Kai Ming Lee is a Lecturer at the Department of Physics within the Faculty of Science at The University of Hong Kong. His research focuses on Quantum Field Theories and Leaky Systems, with significant contributions to computational physics and theoretical optics. Education: B.Sc. from The University of Hong Kong, Ph.D. from Caltech Contact: Room 415A, Chong Yuet Ming Physics Building, kmlee1@hku.hk Dr. Lee's research addresses fundamental problems in theoretical physics, including cellular automaton applications to computational challenges and morphology-dependent resonances in dielectric systems. His publications span journals like International Journal of Modern Physics C and Physical Review E , reflecting interdisciplinary work at the intersection of physics and mathematics. He has served on the Faculty of Science Board at HKU since 2000, with ongoing appointments through 2024. Dr. Lee contributes to academic governance and has participated in knowledge exchange activities, including a 2018 public lecture series on gravitational physics. Teaching: Courses include PHYS1650 'Nature of the Universe' and CCST9056 'The Force is with You: How Things Work'

• Machine Learning
• Non-parametric Methods
• Computational Methods
• +6 more

Yifan Chen is an Assistant Professor in the Department of Computer Science and affiliate faculty in the Department of Mathematics at Hong Kong Baptist University's Faculty of Science. He joined HKBU in Fall 2023 after completing his PhD in Statistics from the University of Illinois Urbana-Champaign in 2023 under the guidance of Prof. Yun Yang. His educational background includes: B.S. in Statistics from Fudan University (2018), advised by Prof. Juan Shen and Prof. Chenghong Zhang Ph.D. in Statistics from University of Illinois Urbana-Champaign (2023), advised by Prof. Yun Yang Dr. Chen's research focuses on developing efficient algorithms for machine learning, with particular emphasis on non-parametric models and neural networks featuring intensive matrix operations. His work bridges statistical theory with practical computational challenges in modern machine learning systems, especially those involving Transformers (language models) and Graph Neural Networks (GNNs). He approaches machine learning from both theoretical and applied perspectives, seeking to understand statistical structures while addressing real-world computational constraints. His publication record shows consistent output in top-tier venues including ICML, NeurIPS, KDD, and EMNLP, with recent work spanning graph coarsening, optimal transport, efficient language model fine-tuning, and causal inference. His research demonstrates strong mathematical foundations combined with practical applications in AI systems. Among his notable achievements: NSFC Young Scientists Fund (2025) GDSTC General Program funding (2024) RGC Early Career Scheme proposal grant (2024) ICML 2023 Grant Award ($1,500) Dr. Chen actively mentors students through his research group, supervising PhD students and visiting research assistants. He has successfully guided students who have gone on to PhD programs at institutions including Institute of Science Tokyo, HKU, Fudan, and NUS. His teaching includes COMP 7070 Advanced Topics in Artificial Intelligence and Machine Learning, which covers core machine learning concepts for AI application research, and COMP 2027 Applied Linear Algebra for Computing. His research group focuses on efficient machine learning algorithms, with current projects spanning graph neural networks, optimal transport, language model efficiency, and causal inference. He collaborates with researchers from institutions including UIUC, Fudan University, and industry labs like Amazon Alexa AI.