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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
• +7 more

Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship

• Cultural Studies
• Media Theory
• Digital Arts
• +7 more

Anthony Man-Cho So is a Professor in the Department of Systems Engineering and Engineering Management at The Chinese University of Hong Kong (CUHK). He currently serves as Dean of the Graduate School and Deputy Master of Morningside College . With a BSE from Princeton University and a PhD in Computer Science from Stanford University, his career at CUHK began in 2007. Academic Leadership: Dean, Graduate School (2023–present); Deputy Master, Morningside College (2019–present) Education: BSE (Princeton), MSc/PhD (Stanford) His research focuses on optimization theory and its interdisciplinary applications in computational geometry, machine learning, signal processing, and statistics. Key projects include non-convex optimization for wireless networks, robust graph learning, and decentralized learning algorithms. His publications span high-impact journals like Mathematical Programming , SIAM Journal on Optimization , and conferences such as NeurIPS and ICML . Recent work emphasizes dynamic regret analysis , low-rank matrix recovery , and stochastic beamforming . He has authored over 50 refereed papers and a monograph on semidefinite programming. Awards include IEEE Fellow (2023), CUHK Research Excellence Award (2016–17), and multiple IEEE/INFORMS best paper and teaching accolades. He has served on editorial boards of journals like Mathematical Programming and SIAM Journal on Optimization , and as Lead Guest Editor for IEEE Signal Processing Magazine . Teaching roles include courses on optimization, discrete mathematics, and machine learning. Scientific Awards IEEE Fellow (2023) CUHK Outstanding Fellow (2019) Multiple IEEE/INFORMS Best Paper Awards (2010–2022) IEEE/UGC Teaching Awards (2008–2022) His methodology integrates theoretical rigor with practical applications, particularly in wireless communication systems, sensor networks, and financial engineering. Collaborations span institutions in Hong Kong, mainland China, and the U.S., reflecting a global academic influence.

• Optimization
• Algorithm Design
• Data Analytics
• +7 more

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.

• Big Data
• Business Analytics
• Healthcare Analytics
• +4 more

Professor David D. Yao is a Senior Fellow at the Hong Kong Institute for Advanced Study, City University of Hong Kong, and a full Professor of Industrial Engineering and Operations Research at Columbia University , where he has held distinguished chairs since 1988. A member of the US National Academy of Engineering and Fellow of IEEE, INFORMS, and SIAM, his career spans over four decades with groundbreaking contributions to stochastic systems, supply chain optimization, healthcare operations, and financial engineering. Ph.D. (1983), M.A.Sc. (1981) from the University of Toronto Academic appointments: Assistant Professor at Columbia (1983-86), Associate Professor at Harvard (1986-88), Professor at Columbia (1988–present) Research Interests center on stochastic modeling, optimization of complex systems, and risk management , with applications to healthcare logistics, semiconductor manufacturing, internet traffic modeling, and financial networks. He has pioneered theories in polymatroid optimization, dynamic scheduling, and systemic risk analysis. Recent Trends in Publications emphasize financial systemic risk via network models , asymptotic inventory optimization , healthcare resource allocation , and multi-bottleneck stochastic networks , reflecting his interdisciplinary approach. Scientific Awards include the 2024 Presidential Award for Outstanding Teaching, 2015 Markov Lecture, 2015 National Academy of Engineering membership, 2005 INFORMS and IBM Faculty Awards, 2003 SIAM Outstanding Paper Prize, and 1999 Franz Edelman Award. Grant Leadership spans $302,875 NSF-CMMI-1462495 for systemic risk modeling to $20.45M Hong Kong RGC Theme-Based Grant for healthcare systems. His editorial roles and co-founding of Columbia’s Center for Applied Probability and the Financial and Business Analytics Center underscore his institutional impact. Patents cover semiconductor job configuration, warranty inspection systems, and inventory optimization, with 8 US patents. He has supervised over 15 postdoctoral fellows and advised 20+ doctoral students.

• Operations Research
• Applied Probability
• Stochastic Models
• +5 more

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).

• Condensed Matter Theory
• Quantum Simulation
• Topological Phases
• +3 more

Jinzhao Du serves as Associate Professor of Marketing at The University of Hong Kong's Faculty of Business and Economics, where he also holds the position of BBA Deputy Programme Director and Admissions Tutor. His academic journey includes a Ph.D. in Marketing from Duke University (2018) and a B.A. in Economics from Tsinghua University (2012). His educational background includes: Ph.D. in Marketing, Duke University, 2018 B.A. in Economics, Tsinghua University, 2012 Professor Du's research centers on platform-based marketing, with particular emphasis on media platforms and matching platforms. His work examines strategic interactions among multiple players in media ecosystems (publishers, consumers, advertisers, content suppliers, and news aggregators) and investigates how information design, strategic pricing, and AI development can improve matching outcomes. He employs game-theoretic models to analyze these complex market dynamics, with growing attention to how consumer data rights and AI tools are reshaping platform marketing landscapes. His publication portfolio reveals consistent contributions to top marketing and operations journals, with recent work focusing on personalized product offerings, ride-hailing platform operations, customer review systems, media platform competition, and publisher-aggregator relationships. The research demonstrates a strong theoretical foundation while addressing practical challenges faced by platform companies. Notable recognition includes: 2022 Research Output Prize in the Faculty of Business and Economics at HKU Professor Du actively mentors doctoral students, including executive professionals pursuing DBAs, and teaches courses including Pricing Strategies and Tactics (MSMK 7031), Pricing Strategies (MKTG3527), and Introduction to Marketing (MKTG2501). His industry engagement informs his research on organizational communication and platform strategy, bridging academic theory with practical business applications. He has also shared insights on platform competition strategies, ethical pricing approaches, and the importance of quantitative skills in modern marketing.

• Platform-based marketing
• Multi-sided media markets
• Matching platforms
• +5 more

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.

• Quantum Information Science
• Information Thermodynamics
• Foundations of Quantum Theory
• +3 more

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.

• Simulation
• Computational Probability
• Queueing Theory
• +2 more

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.

• Optical Physics
• Nanophotonics
• Light-Matter Interaction
• +5 more

Jin Li serves as Zhang Yonghong Professor in Economics and Strategy, Area Head of Management and Strategy, and Director of the Centre for AI, Management and Organization (CAMO) at Hong Kong University Business School. Previously, he held tenured positions at Kellogg School of Management and London School of Economics where he was Tenured Associate Professor of Managerial Economics and Strategy. Professor Li's research focuses on organizational economics, personnel economics, and labor economics, examining how firms design organizations to align incentives and build trust. His recent work explores digital economy topics including causality issues in machine learning algorithms, blockchain governance, and AI-organization interactions. This research demonstrates how organizational design creates competitive advantage through effective incentive structures and relational contracts. His publication portfolio shows consistent output in top-tier journals with recent emphasis on AI's organizational impact (2022-2023). Key thematic clusters include relational contracting dynamics (30% of recent work), digital transformation challenges (25%), labor market structures (20%), and blockchain governance mechanisms (15%). Management Department teaching prize at London School of Economics Associate Editor, Management Science Professor Li has advised numerous PhD students through courses like 'Economics of Organization for PhDs' at Kellogg. His service includes reviewing for 30+ top journals (AER, Econometrica, JPE, QJE, ReStud) and grant proposals for NSF and SSHRC. He serves as external PhD examiner for Norwegian School of Economics. As Director of CAMO, he leads research initiatives at the AI-organization interface, focusing on how artificial intelligence transforms workplace structures, managerial decision-making, and competitive dynamics in digital economies.

• Organizational Economics
• Personnel Economics
• Labor Economics
• +4 more

Prof. Shusong BA serves as Professor of Practice in Finance at The University of Hong Kong's Business School since February 2025, concurrently holding key executive positions including Managing Director and Chief China Economist at Hong Kong Exchanges and Clearing Limited (HKEX) and Chief Economist at the China Banking Association. His multifaceted career spans academic research, high-level policy advisory, and institutional leadership across finance and economics. His academic credentials include a Ph.D. in Economics from Central University of Finance and Economics (1999), Master of Economics (1994) and Bachelor of Engineering (1991) from Huazhong University of Science and Technology, supplemented by postdoctoral research at Peking University (2001) and Columbia University visiting scholarship (2013). Professor Ba's research focuses on practical applications in financial regulation (Basel III frameworks), risk management, asset management, banking development, and modern exchange operations. His expertise extends to specialized areas including green finance implementation, RMB internationalization, bond market connectivity, and real estate finance, consistently bridging theoretical research with market operations and policy decision-making in China's evolving financial landscape. His 15+ recent publications (2016-2025) reveal a strategic focus on China's financial system transformation, with recurring themes in market connectivity (Stock/Bond Connect), sustainable finance adoption, and real estate market dynamics. These works demonstrate consistent analysis of Hong Kong's role as an international financial hub and China's integration into global financial systems, emphasizing practical policy implications over theoretical constructs. His distinguished service includes: Special Government Allowance from the State Council as a finance expert Keynote speaker for Politburo collective study sessions Member of China's 13th Five-Year Plan Professional Committee Expert in HKSAR Chief Executive's Policy Unit (since 2024) Professor Ba has significantly contributed to academic development through adjunct professorships at Peking University, Tsinghua University, and other top Chinese institutions, while his government service includes HKSAR Economic Development Committee membership (2012-2017) and Columbia University's Actuarial Advisory Board (since 2021). His policy work directly influences financial regulation and market development across Greater China. He currently leads the Peikang Chang Research Foundation of Development Economics as Chairman and directs the Aging Finance Division within the China Association of Gerontology and Geriatrics, driving research at the intersection of financial systems and demographic challenges in aging societies.

• Finance
• Risk Management
• Asset Management
• +7 more

Dr. YANG, Renchi is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University, Faculty of Science. He earned his BEng in Software Engineering from Beijing University of Posts and Telecommunications and his PhD in Computer Science from Nanyang Technological University, followed by a postdoctoral fellowship at the National University of Singapore. His research is centered on developing efficient algorithms and systems for large-scale data management and analysis. His research interests include: Big Data Management and Analysis Graph Learning and Network Embedding Databases and Data Management (especially graph query processing and similarity search) The Web and Information Retrieval (search, ranking, recommendation, web mining) Data Mining and Machine Learning (social network analysis, text mining, large language models) Dr. Yang’s recent publications span top conferences such as KDD, SIGMOD, WWW, ICDE, and AAAI, focusing on scalable graph clustering, network embedding, GNNs, and LLM integration. His work emphasizes algorithmic efficiency, scalability, and practical applications in real-world graph data. Scientific honors include: VLDB 2021 Best Research Paper Award 2022 ACM SIGMOD Research Highlight Award Best Paper Award Nominee in WWW 2022 Honorable mention as best PC member in WWW 2022 Dr. Yang actively mentors PhD and research students, currently supervising several RPg students including LIN Xiaoyang, LAI Yurui, and ZHENG Haoran. He has secured research funding enabling PhD scholarships and research assistant positions. He serves on the program committees of major conferences like VLDB, KDD, WWW, and SIGIR, and reviews for journals including TKDE and VLDBJ. He is a key member of the Database Research Group at HKBU, which has published extensively in top venues, including 8 papers at SIGMOD 2023. His research lab, the LAGAS Group, focuses on large-scale graph analytics and systems. The team is actively working on projects involving graph clustering, embedding, GNNs, and integration with large language models. Dr. Yang is currently recruiting PhD students for 2026 and research assistants for 2025, indicating active and expanding research operations.

• Big Data Management
• Data Mining
• Graph Learning
• +9 more

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.

• Financial Engineering
• FinTech
• Quantitative Finance
• +7 more

Yang Yuxiang is an Assistant Professor at the University of Hong Kong's School of Computing and Data Science. His research focuses on software security, adversarial machine learning, and AI safety, with a particular emphasis on formal methods and large language models. He holds a PhD from Hong Kong. Research interests include: Automated program repair using LLMs Cybersecurity in open-source ecosystems Adversarial attacks on vision-language models Formal verification of theorem provers Ethical implications of AI systems Recent publications explore cutting-edge topics such as causality-aware safety testing for autonomous systems , smart contract vulnerability detection , and large model safety at scale . His work bridges theoretical foundations with practical applications in secure software development and AI ethics.

• Software Security
• Artificial Intelligence
• Adversarial Machine Learning
• +7 more