HighlightsThese highlights are AI-generated using the faculty's CV and Google Scholar profile
Hady W. Lauw is a leading expert in preference mining, recommender systems, and visual analytics, with internationally recognized contributions to machine learning, web search, and data mining.
Combines methodological innovation in preference mining, explainable AI, and multimodal analytics with practical impact in recommendation, web search, and visual analytics; recognized for bridging theory and real-world applications, and for leadership in academic and professional communities.
Focused research areas include Machine learning for personalized recommendation, comparative explanations, and user preference modeling; visual and semantic analytics; dimensionality reduction; cross-domain and continual learning; explainable recommendation systems; topic modeling and document networks.
Combines methodological innovation in preference mining, explainable AI, and multimodal analytics with practical impact in recommendation, web search, and visual analytics; recognized for bridging theory and real-world applications, and for leadership in academic and professional communities.
Focused research areas include Machine learning for personalized recommendation, comparative explanations, and user preference modeling; visual and semantic analytics; dimensionality reduction; cross-domain and continual learning; explainable recommendation systems; topic modeling and document networks.
Areas of Expertise
Web MiningRepresentation LearningRecommender Systems
Past Awarded Grant
- Slide++: Automatic Augmentation of Academic Slides Towards AI-Enabled Student-Centred Learning, Tertiary Education Research Fund (TRF), Ministry of Education (MOE), PI: Hady W. LAUW, 2022, S$262,196
- Lifelong Learning for Recommender Systems: Continual, Cross-Domain, and Cross-Platform Approaches, Research Programme, AI Singapore, PI: Hady W. LAUW, 2022, S$885,240
- Universal Pre-training of Graph Neural Networks, Academic Research Fund (AcRF) Tier 2, Ministry of Education (MOE), PI: FANG Yuan, Co-PI: Jing JIANG, 2022, S$676,468
- One-Shot Learning: A Crucial Learning Paradigm Towards Human-like Learning, AI Singapore Research Programme, AI Singapore, PI: FANG Yuan, Co-PI: Steven HOI, 2018, S$497,757.6
- Dimensionality Reduction for Recommender Systems: Unified Latent Co-representation of Multi-Modal Preference Signals, NRF Fellowship, National Research Foundation (NRF), PI: Hady W. LAUW, 2016, S$2,704,332
Latest Publications
Showing up to 6 latest publications from the past 5 years.
- K Theocharidis, HW Lauw, P KarrasIEEE Transactions on Computational Social Systems, 2026
- NT Tran, HW LauwProceedings of the 33rd ACM International Conference on Multimedia, 6412-6420, 2025
- A Ledent, P Kasalický, R Alves, HW LauwIEEE Transactions on Neural Networks and Learning Systems, 2025
- HW Lauw, M Najork, E Terzi, P TsaparasACM Transactions on Intelligent Systems and Technology 16 (5), 1-3, 2025
- NT Tran, HW LauwThe 41st Conference on Uncertainty in Artificial Intelligence, 2025
- K Theocharidis, HW LauwACM SIGKDD Explorations Newsletter 27 (1), 32-51, 2025
Qualification
- PhD, Nanyang Technological University, 2008
Teaching Topics
- Computational Thinking
- IS Application Project
