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Kian-Lee TanView profile

Professor

• Query Processing
• Big Data Analytics
• Database Systems
• +5 more

Kian-Lee Tan is a Tan Sri Runme Shaw Senior Professor and Professor of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a Ph.D. (1994), M.S. (1992), and B.Sc. (1st Class Honours) from NUS. His academic career spans decades of contributions to database systems and data analytics. Ph.D. in Computer Science, National University of Singapore (1994) M.S. in Computer Science, National University of Singapore (1992) B.Sc. in Computer Science (1st Class Honours), National University of Singapore As a leading researcher in database systems, Tan focuses on query processing and optimization in multiprocessor/distributed systems, database performance, security, and multimedia information retrieval. His work extends to computational biology applications like genome databases and real-time influence analysis on social streams. His recent publications highlight trends in GPU-accelerated graph analytics, trajectory pattern mining, and computational journalism. These works emphasize parallel processing, performance optimization, and social/media data analysis. IEEE Technical Achievement Award (2013) President Science Awards, Singapore (2011) NUS Graduate School Excellent Mentor Award (2010/2011) Outstanding University Researchers Award (1997/1998) Tan has supervised numerous research projects and mentored students contributing to database systems. He secured significant grants including a US$1 million Ripple Foundation grant (2024) for financial technology education. His editorial roles include ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering. He leads the FinTech Lab at NUS Computing and has served on the VLDB Endowment Board (2012-2017). His work bridges database foundations with emerging applications in AI, fintech, and computational journalism.

WANG YeView profile

Associate Professor

• Sound and Music Computing
• Music Information Retrieval
• eHealth
• +12 more

WANG Ye is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a PhD in Information Technology from Tampere University of Technology, Finland, and has been a tenured faculty member at NUS since 2002, following his industry research role at Nokia Research Center. He is the director of the Sound and Music Computing Lab at NUS, leading cutting-edge research in AI-driven music and health technologies. PhD, Information Technology, Tampere University of Technology, Finland (2002) MSc, Telecommunications, Braunschweig University of Technology, Germany (1993) BSc, Telecommunications, South China University of Technology, China (1983) His research is centered on Sound and Music Computing for Human Health and Potential (SMC4HHP) , with a focus on eHealth, eLearning, mobile/wearable computing, and music information retrieval. His work spans AI for stroke rehabilitation, language learning through singing, singing voice synthesis, and automatic music transcription. He has pioneered systems like SLIONS (language learning via karaoke), CocoLyricist (AI co-creation for stroke recovery), and SinTechSVS (expressive singing voice synthesis). The latest articles highlight a strong trend in AI-driven music and health technologies , particularly in controllable lyric generation, singing voice synthesis, automatic pronunciation assessment, and multimodal music transcription. The research increasingly integrates large language models, explainable AI, fairness, and real-world deployment, reflecting a shift from theoretical exploration to practical, human-centered applications in healthcare and education. Dr. Wang has received numerous scientific honors, including: Best Paper Awards at ACM MM, ISMIR, IEEE ISM, and CHI First Prize, Asia Pacific Assistive, Rehabilitative, and Therapeutic Technologies Challenge (2015) Faculty Teaching Excellence Award, NUS School of Computing (2024) Top Paper Award, ACM Multimedia 2022 AI in Medicine Collaborative Grant for CocoLyricist project He has supervised over 11 PhD and 20 MComp students and is currently guiding six PhD candidates. His grants come from MOE, NRF, A*STAR, Nokia, and Smule. He has served as General Chair of ISMIR2017 and TPC Co-Chair of ICOT2017, and is on the editorial boards of IEEE Transactions on Multimedia and Journal of New Music Research. He has also developed and taught the first course on Sound and Music Computing in Singapore. Dr. Wang leads the Sound and Music Computing Lab (SMC Lab) , a multidisciplinary team exploring the synergy of music computing, AI, mobile technology, and cloud systems for health and education. The lab actively collaborates with medical institutions such as NUS Yong Loo Lin School of Medicine, Singapore General Hospital, and Harvard Medical School, and is currently working on projects in AI-supported language learning, stroke rehabilitation, and intelligent music interfaces.

CHAN Chee YongView profile

Associate Professor

• Database Systems
• Query Processing
• Query Optimization
• +3 more

CHAN Chee Yong is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS) . He earned his Ph.D. in Computer Science from the University of Wisconsin-Madison and holds B.Sc. and M.Sc. degrees in Computer Science from NUS. Education : Ph.D., Computer Science, University of Wisconsin-Madison M.Sc., Computer Science, NUS B.Sc., Computer Science (1st Class Honours), NUS His research focuses on database systems , emphasizing query processing and optimization , transaction management , and database usability . He has contributed extensively to XML data dissemination, skyline computation, and multicore database performance optimization, with publications in venues like ACM SIGMOD, VLDB, and IEEE ICDE. Recent publications show increasing emphasis on join optimization , transaction healing , and spatial-keyword queries , reflecting trends in multicore systems, complex query processing, and XML data management. His work combines theoretical rigor with practical applications in distributed databases and data engineering. Notable professional roles include Associate Editor for the VLDB Journal , ACM SIGMOD Record , and IEEE Transactions on Knowledge and Data Engineering . He has served on program committees for major conferences like SIGMOD, ICDE, and VLDB across 2003-2026. Dr. Chan has supervised 9 PhD students and 10 M.Sc./M.Comp. students , including WANG TaiNing (2021), LI Meiying (2020), and TRAN Quoc Trung (2011). His advisees have been placed in institutions like the Institute for Infocomm Research and Huawei Shannon Lab.

Ooi Beng ChinView profile

Professor

• Database Systems
• Distributed Systems
• Blockchain
• +6 more

Ooi Beng Chin is a Professor at the School of Computing , National University of Singapore (NUS). He holds concurrent roles as an adjunct Chang Jiang Professor at Zhejiang University, Visiting Distinguished Professor at Tsinghua University, and Director of NUS AI Innovation and Commercialization Centre in Suzhou, China. He earned his B.Sc. (1st Class Honours, 1985) and Ph.D. (1989) from Monash University, Australia. His research spans database systems, blockchain, machine learning, and large-scale analytics , focusing on system architectures, security, and cross-domain applications. Notable contributions include initiating the Apache SINGA distributed deep learning platform and developing Blockbench, the first blockchain benchmarking system. He also co-founded MZH Technologies (2018) for healthcare analytics. Key publications highlight his work in blockchain-database integration, AI for healthcare/finance, and 5G-enabled data systems. Awards include the ACM SIGMOD EF Codd Innovation Award (2020), Singapore President's Science Award (2011), and fellowships from SNAS, IEEE, ACM , and SAEng (2023). He leads the Singapore Blockchain Innovation Programme (SBIP) and contributes to industry collaborations with healthcare institutions and financial organizations. Fellow, Singapore National Academy of Science (SNAS) Fellow, IEEE Fellow, ACM Singapore President's Science Award, 2011 IEEE Kanai Award, 2012 NUS Outstanding Researcher Award, 2013 ACM SIGMOD EF Codd Innovation Award, 2020 Foreign Member, Chinese Academy of Sciences, 2023

Anthony TUNG Kum HoeView profile

Professor

• Database Systems
• Indexing and Searching Complex Objects
• Time Series Analysis
• +13 more

Anthony TUNG Kum Hoe is a Professor in the Department of Computer Science at the National University of Singapore (NUS), where he has established himself as a leading researcher in database systems and data mining. He is also affiliated with the NUS Graduate School for Integrative Sciences and Engineering and serves as a SINGA supervisor. His educational background includes a Ph.D. in Computer Science from Simon Fraser University (2001), an M.Sc. in Information Systems & Computer Science from NUS (1998), and a B.Sc. with 2nd Class Upper Honours in Information Systems & Computer Science from NUS (1997). Professor Tung's research spans several interconnected areas within database systems and data mining. His primary focus is on developing efficient methods for indexing and searching complex data structures including time series, trajectories, trees, graphs, and high-dimensional objects. He has pioneered work in visual query processing, keyword search, and ranking systems. His GENIE (Generic Inverted Index) and LAMP (semi-Lazy Mining Paradigm) projects represent significant contributions to big data analytics, particularly in handling the 'variety' aspect of big data by providing unified frameworks for processing diverse data structures while preserving semantic meaning. His research bridges theoretical database concepts with practical applications in visual data mining, collaborative analytics, and just-in-time model construction. His recent publications reveal a clear evolution from traditional database research toward more complex analytics on diverse data types. While maintaining his core expertise in database indexing and query processing, his work has expanded to incorporate machine learning techniques, particularly in areas like nearest neighbor search, anomaly detection, and predictive analytics. There's a noticeable trend toward interdisciplinary applications, with publications spanning computer vision, natural language processing, transportation systems, and social computing. His research group consistently publishes in top-tier venues including SIGMOD, VLDB, ICDE, and KDD, demonstrating both theoretical rigor and practical relevance. 2005 Best Paper Award for 'Indexing DNA Sequences Using q-grams' 2007 Invited panel speaker on 'Advice for a successful database researcher career in Asia' at SIGMOD 2010 Guest Lecturer for VLDB Database School 2012 VLDB 2012 Research PC Co-chairs 2015 10 Years Best Paper Award, DASFAA 2015 Invited to SIGMOD 2008 and SIGKDD 2008 Program Committees Professor Tung has supervised numerous PhD students and research associates throughout his career, including notable researchers like Zhang Zhenjie (recipient of the 2007 President Graduate Fellowship) and Wang Nan (published in SIGMOD'08). His research group has been consistently productive, with students publishing in top conferences including SIGMOD, ICDE, and VLDB. His professional service is extensive, having served as PC Chair for COMAD'06, Research PC Co-chair for VLDB 2012, and on program committees for virtually all major database and data mining conferences over the past two decades. His research has been supported by various grants that have enabled significant contributions to database technology. His GENIE and LAMP projects represent a cohesive research direction focused on developing systematic approaches to big data analytics. GENIE provides a unified platform for storage and retrieval of big data with various structures, while LAMP introduces a novel paradigm for predictive analytics that combines the strengths of lazy and eager learning approaches. These projects have evolved to incorporate GPU acceleration and parallel processing capabilities, reflecting his commitment to addressing real-world scalability challenges in data-intensive applications.

• Cybersecurity
• Privacy-Preserving Computation
• Cryptography
• +2 more

Dr. YANG Guomin is an Associate Professor of Computer Science at Singapore Management University's School of Computing and Information Systems, where he coordinates the BSc Cybersecurity Track. His research focuses on privacy-preserving cryptography, authentication systems, and secure IoT frameworks. Research spans cryptographic protocols for cloud security, blockchain applications, and federated learning with emphases on efficiency and practical implementation. Recent publications demonstrate innovations in threshold authentication, redactable blockchains, and privacy-aware communication protocols. Advisees include LI Huilin and WANG Jiaheng, with research projects examining hardware-enhanced encryption, biometric authentication policies, and space network security. Work consistently addresses tension between security guarantees and computational efficiency in distributed systems.

Reuben NgView profile

Assistant Professor

• Ageism
• Social Gerontology
• Quantitative Social Science
• +4 more

Dr. Reuben Ng is an Assistant Professor at the Lee Kuan Yew School of Public Policy, National University of Singapore, and Lead Scientist at the Lloyd’s Register Foundation Institute for the Public Understanding of Risk. He holds a PhD in Public Health from Yale University, an MSc in Management Research from the University of Oxford, and degrees from NUS and NTU in Psychology. His research focuses on ageism, social gerontology, and quantitative social science, with a particular emphasis on leveraging behavioral insights and data analytics for evidence-based policymaking. He has contributed to Singapore’s Smart Nation initiatives and advised on risk communication strategies. Over $3.2M in research grants as PI and $4M as PI/Co-PI/Co-I. 50+ peer-reviewed publications and 85 conference presentations globally. Awards include the International Fulbright Science and Technology Award and the Harkness Fellowship. Dr. Ng serves on advisory boards in finance, defense, education, and sustainability. He leads workshops blending data analytics, behavioral insights, and design thinking. His work has been featured in major media outlets like The New York Times, The Guardian, and CNN, and he is ranked in the top 2% of global scientists by Stanford University.

• Programming Languages
• Software Engineering
• Compilers
• +5 more

Manuel Rigger is an Assistant Professor at the National University of Singapore in the School of Computing and leads the Trustworthy Engineering of Software Technologies (TEST) Lab . His research focuses on improving data-centric systems , particularly their reliability, having found over 1,000 unique bugs in database systems. Education : PhD in Computer Science (2019) and MSc in Software Engineering (2015) from Johannes Kepler University Linz; MPhil in Chinese Philosophy (2015) from Xiamen University Research Highlights : Developed SQLancer – an automated testing framework that found 500+ bugs in DBMSs; created Query Plan Guidance (QPG) for efficient logic bug detection; received best paper awards at ICSE '23 and EuroSys '24 Scientific Awards : Recipient of 6 distinguished artifact/reviewer awards Major industry support from Google, AWS, and Microsoft Developed tools adopted by Oracle GraalVM and SQLite Teaching : Lecturer for CS3213 Foundations of Software Engineering and CS6223 Advanced Topics in Software Testing . Supervises multiple PhD/MSc theses on database testing and compiler reliability.

Swapna GottipatiView profile

Associate Professor

• Artificial Intelligence
• Data Science
• Machine Learning
• +7 more

Swapna Gottipati is a Full-time Associate Professor of Information Systems (Education) and Associate Dean (Undergraduate Education) at the School of Computing and Information Systems , Singapore Management University . Holding a PhD from SMU (2014) , she specializes in text analytics, education technology, and digital business. Current focus areas: Artificial Intelligence, Data Science, Technology-Enhanced Learning Interdisciplinary applications: Health Informatics, Social Media Analytics Research Interests span text analytics, opinion mining, curriculum analytics, and digital transformation. She applies machine learning and data mining to educational systems, business processes, and health domains. Scientific Contributions: 2016 Best Paper Award (AIS SIG-ED) 2016 MOE TRF Grant 2017-2020 Conference Best Paper Nominations 2013 Best Paper Finalist (CIKM) Academic Leadership includes: Director of Undergraduate Education Co-developer of SMU-X pedagogy Founder of MyCompetencies mobile platform Organizer of curriculum analytics workshops Grant Projects include the Learning Analytics on Qualitative Student Feedback system (MOE TRF 2016) and ICDL-funded digital literacy studies. She has delivered 12+ invited talks on digital transformation in education and industry.

Xiaokui XiaoView profile

Professor

• Data Management
• Data Analytics
• Data Privacy
• +5 more

Prof. Xiaokui Xiao is a Professor and Deputy Head (Research & Graduate Matters) at the Department of Computer Science, National University of Singapore (NUS). He previously held an Associate Professor position at Nanyang Technological University (NTU). His academic journey includes a PhD from the Chinese University of Hong Kong (2008) and a postdoctoral stint at Cornell University. His research focuses on data management and analytics, with emphasis on large data algorithms, privacy (e.g., differential privacy), and data mining. Notable contributions include the PrivBayes system for private data release and scalable network embedding techniques. Awarded the 2024 ACM SIGMOD Test-of-Time Award, IEEE Fellowship (2022), and ACM Distinguished Membership (2021), Xiao is also a trustee of the VLDB Endowment and Editor-in-Chief of Proceedings of the VLDB Endowment . He has advised over 30 PhD students and researchers, many of whom hold academic or industry leadership roles. His work bridges theoretical foundations with practical systems, addressing challenges in privacy, scalability, and machine learning integration.

• Artificial Intelligence
• Data Science
• Machine Learning
• +9 more

Qianru Sun is an Associate Professor at the School of Computing and Information Systems, Singapore Management University (SMU), and a Lee Kong Chian Fellow. Her research focuses on artificial intelligence, machine learning, computer vision, and semantic segmentation, with a particular emphasis on few-shot learning, meta-learning, and domain adaptation in remote-sensing imagery. Recent publications highlight her work on visual chain-of-thought reasoning , 3D scene understanding via 2D models , and parameter-efficient fine-tuning of large models. Her research also extends to weakly-supervised semantic segmentation and cross-modal video retrieval . Scientific Awards : Lee Kong Chian Fellow (2021–2023, 2025–2027) Outstanding Service Award by MMAsia (2020) Outstanding Reviewer at NeurIPS'21 and ICLR'21 Students : PhD students: Luo Zilin, Tian Zichen, Ying Jiahao Master’s students: Bao Chunhui, LOH Yi Lin, MA Li

• Artificial Intelligence and Data Science
• Data Management & Mining
• Machine Learning & Intelligence
• +3 more

ZHENG Baihua serves as Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS), concurrently holding leadership roles as Associate Dean for SCIS Post-Graduate Research Programmes and Director of the Master of Science in Computing programme. Currently on leave but maintaining full-time faculty status, his academic career spans over two decades with foundational training from Hong Kong University of Science and Technology. Professor Zheng's research program integrates artificial intelligence, data science, and urban computing to solve critical challenges in mobility and sustainability. His expertise centers on trajectory data management, social network analysis, and spatio-temporal modeling, with significant contributions to trajectory compression algorithms, influence minimization in social networks, and real-time traffic prediction systems. His work bridges theoretical database innovations with practical applications in smart city infrastructure and public health interventions. Analysis of recent publications (2024-2025) reveals a dominant focus on physics-informed trajectory processing, GPU-accelerated indexing for high-dimensional data, and transformer-based models for urban mobility prediction. Key trends include the fusion of graph neural networks with spatio-temporal dynamics, novel approaches to contact tracing through timeline graphs, and differentiable search techniques for structured data discovery. These works consistently target real-world deployment in transportation systems and epidemic control. No scientific awards are documented in available institutional records. Information regarding student supervision, research grants, laboratory facilities, or collaborative teams remains unspecified in current public profiles.

Roland YAP Hock ChuanView profile

Associate Professor

• Artificial Intelligence
• Constraints
• Data Analytics
• +4 more

Roland YAP Hock Chuan serves as an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), and previously held the role of assistant director at The Logistics Institute Asia Pacific (TLI-AP). His academic foundation was built at Monash University, Australia, where he earned comprehensive qualifications in Computer Science. Education: Ph.D. in Computer Science, Monash University, Australia M.Sc. in Computer Science, Monash University, Australia B.Sc. (Honours) in Computer Science, Monash University, Australia Research Focus: Renowned for pioneering the CLP(R) system that revolutionized Constraint Programming, Prof. Yap's work now spans artificial intelligence, security, programming languages, and social networks. His research bridges theoretical rigor with real-world applications, particularly in data analytics and knowledge compilation for industrial systems. Publication Evolution: His scholarly output reveals a strategic progression from foundational constraint logic programming (1990s) to cutting-edge security mechanisms and AI-driven solutions (2010s). Recent works demonstrate expertise in robust search algorithms, memory protection systems, and social network defense strategies, reflecting continuous adaptation to emerging computational challenges. Scientific Recognition: Best student paper award at SCA 2011 for social network research Best student runner-up paper at CIKM 2009 1995 Australian Computer Science Ph.D. Prize (1996) Praxa Computer Prize for theoretical computing achievements (1985) Academic Leadership: Prof. Yap directs the Tier 1 research project 'Investigating Product Configuration as Knowledge Compilation,' developing accelerated industrial solvers through innovative KC integration. His teaching portfolio includes advanced security courses (CS4239/5439/6231), shaping next-generation cybersecurity expertise. Mentoring excellence is evidenced by multiple student award-winning publications in top-tier conferences. Collaborative Infrastructure: Through his leadership role at TLI-AP, he contributes to NUS's interdisciplinary logistics research ecosystem, connecting computer science with supply chain innovation and operational optimization challenges.

YANG YaxiView profile

Research Fellow

• Secure Computation
• Applied Cryptography
• Privacy Preserving Data Processing
• +3 more

Dr. YANG Yaxi is a Research Fellow at iTrust, Singapore University of Technology and Design (SUTD), Singapore. She specializes in secure computation, applied cryptography, and privacy-preserving data processing. Her work emphasizes cryptographic techniques for real-world data challenges, including genomic data security, query optimization, and protecting against malicious actors. She holds a B.Sc. (2017) and Ph.D. (2023) in Information Security from Jinan University, Guangzhou, China. Her research interests focus on developing systems that ensure data privacy while maintaining computational efficiency, such as privacy-preserving queries, secure multi-party computation, and protocols for large-scale databases. Her recent articles explore advancements in technologies like oblivious PRFs, range-constrained intersection queries, and certificate-based encryption. These contributions highlight her commitment to enhancing security in outsourced environments and biomedical applications. Dr. Yang collaborates within the iTrust research group at SUTD, which specializes in trustworthy computing and information security. Her work addresses cutting-edge issues in privacy-preserving data processing and secure collaborative systems.

DENG YangView profile

Assistant Professor

• Natural Language Processing
• Information Retrieval
• Large Language Models
• +7 more

Dr. Yang Deng is a tenure-track Assistant Professor at the School of Computing and Information Systems, Singapore Management University, and a Lee Kong Chian Fellow. Previously, he was a Postdoctoral Research Fellow at NExT++ (National University of Singapore). His research focuses on Natural Language Processing, Information Retrieval, and Large Language Models, with special interests in Proactive Conversational AI, Trustworthiness of LLMs, and Human-Centered Information Seeking. He has published over 40 papers in top-tier venues including ACL, EMNLP, WWW, and SIGIR. PhD from The Chinese University of Hong Kong (2023) Research Advisor to CHEANG Chi Seng Research Domains: Natural Language Processing Information Retrieval Large Language Models Human-Agent Interaction Digital Transformation Trustworthy AI Scientific Recognition: Lee Kong Chian Fellowship Google South Asia & Southeast Asia Research Awards 2024 EMNLP 2024 Outstanding Area Chair NeurIPS 2024 Best Reviewer