Yatao Bian
Assistant Professor
Develops machine learning for scientific discovery, including AI for drug discovery and models of molecules and proteins.
Yatao Bian's lab at NUS works on proteins, drugs & materials. 39 papers since 2023, 34 at top venues, mostly NeurIPS and ICLR. 3 PhD students. 24 alumni, most often to Tencent and Apple. Applications close .
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 87%
- PhD students
- 3
- MS students
- 0
- alumni listed
- 24
Papers by yearfrom DBLP, 2023–2026
- 6 papers2026 · T1 5 · collecting
- 11 papers2025 · T1 10
- 10 papers2024 · T1 8
- 12 papers2023 · T1 11
T1 venuesOtherVenues: NeurIPS, ICLR, ICML, AAAI, ACL
Research focuspaper titles that use each topic's words
- Proteins, drugs & materials3 papers
- discovery2 papers
- molecules0 papers
- proteins0 papers
- scientific discovery0 papers
Paper list
From DBLP.
20266 papers
- ACL (T1)A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions (opens in a new tab)
- AAAI (T1)CrystalDiT: Simple Diffusion Transformers for Crystal Generation (opens in a new tab)
- Inf. Process. Manag.Learning hierarchical time-frequency representation for long-term time series forecasting (opens in a new tab)
- SIGIR (T1)Question-Adaptive Graph Learning for Multi-hop Retrieval Augmented Generation (opens in a new tab)
- KDD (T1)Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation (opens in a new tab)
- ECCV (T1)StoryBlender: Inter-shot Consistent and Editable 3D Storyboard with Spatial-Temporal Dynamics (opens in a new tab)
202511 papers
- NeurIPS (T1)3D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding (opens in a new tab)
- TPAMI (T1)A Unified Random Walk, Its Induced Laplacians and Spectral Convolutions for Deep Hypergraph Learning (opens in a new tab)
- ICLR (T1)COME: Test-time Adaption by Conservatively Minimizing Entropy (opens in a new tab)
- ICLR (T1)Erasing Concept Combination from Text-to-Image Diffusion Model (opens in a new tab)
- ICML (T1)Hierarchical Graph Tokenization for Molecule-Language Alignment (opens in a new tab)
- ICLR (T1)InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization (opens in a new tab)
- NeurIPS (T1)Learning to Learn with Contrastive Meta-Objective (opens in a new tab)
- ICML (T1)Measuring Diversity in Synthetic Datasets (opens in a new tab)
- Findings of ACLRelEdit: Evaluating Conceptual Knowledge Editing in Language Models via Relational Reasoning (opens in a new tab)
- NeurIPS (T1)Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization (opens in a new tab)
- IJCAI (T1)Unified Molecule-Text Language Model with Discrete Token Representation (opens in a new tab)
202410 papers
- Journal of Chemical Information and ModelingCan Pretrained Models Really Learn Better Molecular Representations for AI-Aided Drug Discovery? (opens in a new tab)
- ICLR (T1)EBMDock: Neural Probabilistic Protein-Protein Docking via a Differentiable Energy Model (opens in a new tab)
- ICLR (T1)Enhancing Neural Subset Selection: Integrating Background Information into Set Representations (opens in a new tab)
- ICML (T1)How Interpretable Are Interpretable Graph Neural Networks? (opens in a new tab)
- KDD (T1)One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes (opens in a new tab)
- TPAMI (T1)Recognizing Predictive Substructures With Subgraph Information Bottleneck (opens in a new tab)
- WSDM (T1)Rethinking and Simplifying Bootstrapped Graph Latents (opens in a new tab)
- NeurIPS (T1)The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection (opens in a new tab)
- ACM Trans. Knowl. Discov. DataVariate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection (opens in a new tab)
- ACL (T1)WatME: Towards Lossless Watermarking Through Lexical Redundancy (opens in a new tab)
202312 papers
- ICLR (T1)BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion (opens in a new tab)
- EMNLP (T1)Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators (opens in a new tab)
- WWW (T1)Curriculum Graph Poisoning (opens in a new tab)
- NeurIPS (T1)Does Invariant Graph Learning via Environment Augmentation Learn Invariance? (opens in a new tab)
- AAAI (T1)DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - a Focus on Affinity Prediction Problems with Noise Annotations (opens in a new tab)
- NeurIPS (T1)Fairness-guided Few-shot Prompting for Large Language Models (opens in a new tab)
- NeurIPS (T1)Learning Invariant Molecular Representation in Latent Discrete Space (opens in a new tab)
- ICLR (T1)Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization (opens in a new tab)
- Findings of EMNLPRECAL: Sample-Relation Guided Confidence Calibration over Tabular Data (opens in a new tab)
- CIKM (T1)SAILOR: Structural Augmentation Based Tail Node Representation Learning (opens in a new tab)
- NeurIPS (T1)Simplifying and Empowering Transformers for Large-Graph Representations (opens in a new tab)
- NeurIPS (T1)Understanding and Improving Feature Learning for Out-of-Distribution Generalization (opens in a new tab)
Where alumni went24 listed, 33% to industry
Industry 4Academia 8
Most often to
- Tencent
- Apple
- Huawei
Also to
- EPFL
- ETH Zurich
- Imperial College London
Apply to NUSFall 2027
School of Computing PhD in Computer Science
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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