Irwin King
Professor
Works on machine learning, graph neural networks, recommender systems, social computing and natural language processing.
Irwin King's lab at CUHK works on graph learning, social computing & responsible AI and recommendation, search & web. 141 papers since 2023, 89 at top venues, mostly WWW and KDD. 21 PhD students and 6 master's students. 10 alumni. Applications close .
At a glance
- papers, 2023–2026
- 37/ year
- at T1 venues
- 63%
- PhD students
- 21
- MS students
- 6
- alumni listed
- 10
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 32 papers2026 · T1 21 · collecting
- 31 papers2025 · T1 20
- 43 papers2024 · T1 23
- 35 papers2023 · T1 25
T1 venuesOtherVenues: WWW, KDD, AAAI, IJCNN, TKDE
Research focuspaper titles that use each topic's words
- Graph learning67 papers
- Recommendation, search & web11 papers
- recommender1 paper
- Social computing & responsible AI0 papers
- social computing0 papers
Paper list
From the lab homepage and DBLP.
202632 papers
- IEEE Trans. Neural Networks Learn. Syst.A Survey on Vision-Language-Action Models for Embodied AI (opens in a new tab)
- AAMAS (T1)Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning (opens in a new tab)
- ICLR (T1)Adversarial Encoding Perturbation and Synthesis for Set Representation Auxiliary Learning (opens in a new tab)
- IEEE Signal Process. Mag.Artificial Intelligence for Education: A Signal Processing Perspective: Part II: From Human-AI Cocreativity to Educational Equity [From the Guest Editors] (opens in a new tab)
- TPAMI (T1)CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey (opens in a new tab)
- AAAI (T1)ConSurv: Multimodal Continual Learning for Survival Analysis (opens in a new tab)
- TPAMI (T1)Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey (opens in a new tab)
- Trans. Mach. Learn. Res.Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing (opens in a new tab)
- ICLR (T1)Exploiting Low-Dimensional Manifold of Features for Few-Shot Whole Slide Image Classification (opens in a new tab)
- WWW (T1)FL@FM-TheWebConf'26: The 3rd International Workshop on Federated Foundation Models for the Web (opens in a new tab)
- Educ. Inf. Technol.From disengaged to self-determined: A latent transition analysis of students' AI learning motivation (opens in a new tab)
- KDD (T1)From Evidence to Trajectory: Abductive Reasoning Path Synthesis for Retrieval-Augmented Generation Agents Development (opens in a new tab)
202531 papers
- Educ. Inf. Technol.A phenomenographic approach to students' conceptions of learning artificial intelligence (AI) in secondary schools (opens in a new tab)
- ACM Comput. Surv.A Survey of Text Watermarking in the Era of Large Language Models (opens in a new tab)
- SIGWEB Newsl.ACM SIGWEB - Annual Report 2025 (opens in a new tab)
- IEEE Signal Process. Mag.Artificial Intelligience for Education: A Signal Processing Perspective: Part I: From Active Learning to Mitigating Gender Bias [From The Guest Editors] (opens in a new tab)
- EMNLP (T1)Astra: Efficient Transformer Architecture and Contrastive Dynamics Learning for Embodied Instruction Following (opens in a new tab)
- ACL (T1)Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation? (opens in a new tab)
- RECOMBcfDecon: Accurate and Interpretable Methylation-Based Cell Type Deconvolution for Cell-Free DNA (opens in a new tab)
- AAAI (T1)Context-aware Inductive Knowledge Graph Completion with Latent Type Constraints and Subgraph Reasoning (opens in a new tab)
- TKDE (T1)Deep Graph Anomaly Detection: A Survey and New Perspectives (opens in a new tab)
- KDD (T1)Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature Aggregation (opens in a new tab)
- NAACL (T1)Entropy-Based Decoding for Retrieval-Augmented Large Language Models (opens in a new tab)
- Comput. Educ. Artif. Intell.Epistemic network analysis of in-service teachers' competency to teach artificial intelligence for secondary education (opens in a new tab)
202443 papers
- AAAI (T1)A Diffusion-Based Pre-training Framework for Crystal Property Prediction (opens in a new tab)
- ACM Trans. Intell. Syst. Technol.A Survey of Trustworthy Federated Learning: Issues, Solutions, and Challenges (opens in a new tab)
- TPAMI (T1)A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection (opens in a new tab)
- IJCAI (T1)A Systematic Survey on Federated Semi-supervised Learning (opens in a new tab)
- ACL (T1)An Entropy-based Text Watermarking Detection Method (opens in a new tab)
- ICLR (T1)An Unforgeable Publicly Verifiable Watermark for Large Language Models (opens in a new tab)
- IJCNNAnomaly Detection on Attributed Network Based on Hyperbolic Radial Distance (opens in a new tab)
- Findings of EMNLPCLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models (opens in a new tab)
- ICONIPCombining Explicit Priors and Set Attention Driven Implicit Priors for Demonstration-Guided Reinforcement Learning (opens in a new tab)
- BIBMData Augmentation Techniques for Chinese Disease Name Normalization (opens in a new tab)
- Nat. Comput. Sci.Deep generative design of RNA aptamers using structural predictions (opens in a new tab)
- AAAI (T1)Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks (opens in a new tab)
202335 papers
- WWW (T1)1st Workshop on Federated Learning Technologies (opens in a new tab)
- Educ. Inf. Technol.A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools (opens in a new tab)
- WWW (T1)A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness and Privacy (opens in a new tab)
- TKDE (T1)A Survey on Deep Semi-Supervised Learning (opens in a new tab)
- Inf. FusionA survey on graph embedding techniques for biomedical data: Methods and applications (opens in a new tab)
- IJCAI (T1)A Unified View of Deep Learning for Reaction and Retrosynthesis Prediction: Current Status and Future Challenges (opens in a new tab)
- TALEAn experiential learning approach to learn AI in an online workshop (opens in a new tab)
- WWW (T1)Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space (opens in a new tab)
- TKDE (T1)CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs (opens in a new tab)
- KDD (T1)Contrastive Cross-scale Graph Knowledge Synergy (opens in a new tab)
- IJCAI (T1)Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classification (opens in a new tab)
- IJCAI (T1)Doubly Stochastic Graph-based Non-autoregressive Reaction Prediction (opens in a new tab)
Where alumni went10 listed
Apply to CUHKFall 2027
Computer Science and Engineering MPhil/PhD
- Round
- HKPFS / main round
- Opens
- —
- GRE
- See program page
- English
- Interview in English
- Fee
- See program page
Not yet confirmed for this intake.
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