Bryan Hooi
Assistant Professor
Works on machine learning for graphs, anomaly detection, spatiotemporal data and reliability of vision-language models.
Bryan Hooi's lab at NUS works on time series, anomaly & spatio-temporal data, graph mining & networks and vision-language & multimodal. 101 papers since 2023, 76 at top venues, mostly ICML and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 26/ year
- at T1 venues
- 75%
- PhD students
- 0
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 22 papers2026 · T1 13 · collecting
- 37 papers2025 · T1 27
- 21 papers2024 · T1 17
- 21 papers2023 · T1 19
T1 venuesOtherVenues: ICML, NeurIPS, ICLR, ACL, Findings of EMNLP
Research focuspaper titles that use each topic's words
- Vision-language & multimodal28 papers
- Graph mining & networks24 papers
- Time series, anomaly & spatio-temporal data12 papers
- spatiotemporal data0 papers
- spatiotemporal0 papers
Paper list
From the lab homepage.
202622 papers
- Findings of EMNLPAgentSwing: Adaptive Parallel Context Management Routing for Long-Horizon Web Agents (opens in a new tab)
- ICML (T1)AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing (opens in a new tab)
- Findings of EMNLPBetter with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notes (opens in a new tab)
- ACL FindingsBeyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models (opens in a new tab)
- ICML (T1)Conversation for Non-verifiable Learning: Self-Evolving Large Language Models through Meta-Evaluation (opens in a new tab)
- ICLR (T1)EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic Systems (opens in a new tab)
- ICML AI4Science Workshop, Best Paper AwardFABSCORE: Fine-Grained Evaluation of Fabrications in Automated AI Research (opens in a new tab)
- EMNLP (T1)FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search (opens in a new tab)
- ICML (T1)Just-In-Time Reinforcement Learning: Continual Learning in LLM Agents Without Gradient Updates (opens in a new tab)
- ICML (T1)Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents (opens in a new tab)
- ACL FindingsMeta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models (opens in a new tab)
- NeurIPS (T1)MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome (opens in a new tab)
202537 papers
- ICML (T1)Adapting Precomputed Features for Efficient Graph Condensation
- EMNLP (T1)Automating Steering for Safe Multimodal Large Language Models (opens in a new tab)
- Findings of EMNLPBackdoor-Powered Prompt Injection Attacks Nullify Defense Methods
- ACL (T1)Can Indirect Prompt Injection Attacks Be Detected and Removed? (opens in a new tab)
- ACL (T1)Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study Over Open-ended Question Answering (opens in a new tab)
- ICLR (T1)CHiP: Cross-modal Hierarchical Direct Preference Optimization for Multimodal LLMs
- COLING (T1)Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding (opens in a new tab)
- NeurIPS (T1)ConfTuner: Training Large Language Models to Express Their Confidence Verbally (opens in a new tab)
- ACL (T1)Defense Against Prompt Injection Attack by Leveraging Attack Techniques
- Findings of ACLDRS: Deep Question Reformulation With Structured Output (opens in a new tab)
- EMNLP (T1)Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance (opens in a new tab)
- Findings of EMNLPEnhancing Multi-Agent Debate System Performance via Confidence Expression
202421 papers
- ICLR (T1)Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs (opens in a new tab)
- ICLR (T1)Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision
- TKDE (T1)Efficient Heterogeneous Graph Learning via Random Projection (opens in a new tab)
- ACL (T1)Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View (opens in a new tab)
- KDD (T1)Fake News in Sheep’s Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks (opens in a new tab)
- NeurIPS (T1)G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering (opens in a new tab)
- ICLR (T1)Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning (opens in a new tab)
- NeurIPS (T1)ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition
- TKDE (T1)Interrelated Dense Pattern Detection in Multilayer Networks
- USENIX Security (T1)KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection (opens in a new tab)
- ECCV (T1)Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning (opens in a new tab)
- TKDE (T1)MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering (opens in a new tab)
202321 papers
- ICML (T1)A Generalization of ViT/MLP-Mixer to Graphs (opens in a new tab)
- ICDE (T1)Construction and Applications of Billion-Scale Pre-trained Multimodal Business Knowledge Graph (opens in a new tab)
- KDD (T1)DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection (opens in a new tab)
- TPAMI (T1)Deep Long-Tailed Learning: A Survey (opens in a new tab)
- NeurIPS (T1)Expanding Small-Scale Datasets with Guided Imagination (opens in a new tab)
- WSDM (T1)Graph Explicit Neural Networks: Explicitly Encoding Graphs for Efficient and Accurate Inference (opens in a new tab)
- ICML (T1)GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks (opens in a new tab)
- ICML (T1)Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement (opens in a new tab)
- CoNLLHow Fragile is Relation Extraction under Entity Replacements?
- NeurIPS (T1)LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting (opens in a new tab)
- EMNLP (T1)Primacy Effect of ChatGPT
- CVPR (T1)Probabilistic Knowledge Distillation for Face Ensembles (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NUSFall 2027
School of Computing PhD in Computer Science
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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Data
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