Yang Yang
Professor
Studies AI on large-scale graph and time-series data, including self-supervised and foundation models for brain signals such as epileptic-wave detection.
Yang Yang's lab at Zhejiang works on graph mining & networks, generative & foundation models and recognition, detection & segmentation. 53 papers since 2023, 35 at top venues, mostly NeurIPS and AAAI. 16 PhD students and 10 master's students. 40 alumni, most often to Alibaba and ByteDance. Applications close .
At a glance
- papers, 2023–2026
- 14/ year
- at T1 venues
- 66%
- PhD students
- 16
- MS students
- 10
- alumni listed
- 40
Papers by yearfrom the lab homepage, 2023–2026
- 9 papers2026 · T1 7 · collecting
- 11 papers2025 · T1 5
- 21 papers2024 · T1 15
- 12 papers2023 · T1 8
T1 venuesOtherVenues: NeurIPS, AAAI, WWW, EMNLP, ICLR
Research focuspaper titles that use each topic's words
- Graph mining & networks14 papers
- Generative & foundation models5 papers
- Recognition, detection & segmentation3 papers
- signals2 papers
- time-series0 papers
Paper list
From the lab homepage.
20269 papers
- IJCAI (T1)[Code]
- ICLR (T1)Assembling the Mind‘s Mosaic: Towards EEG Semantic Intent Decoding
- ECML-PKDDLearning Pairwise Cooperation For Large-scale Vertex Subset Selection: Dominating Set Problem as Example
- WWW (T1)PolicySim: An LLM-Based Agent Social Simulation Sandbox for Proactive Policy Optimization
- EMNLP (T1)PTCG-Bench: Can LLM Agents Master Pokémon Trading Card Game?
- EMNLP (T1)RAT: RunAnyThing via Fully Automated Environment Configuration
- EMNLP (T1)Self-Correcting Agentic RAG via Memory-Grounded Failure Localization
- AAAI (T1)Trimming the Fat: Redundancy-Aware Acceleration Framework for DGNNs
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningUnified Spatio-Temporal Tokens are Bases for Generalizable Traffic Forecasting
202511 papers
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningASTNet: Asynchronous Spatio-Temporal Network for Large-Scale Chemical Sensor Forecasting
- NeurIPS (T1)Cypher-RI: Reinforcement Learning for Integrating Schema Selection into Cypher Generation
- IEEE Reviews in Biomedical EngineeringDeep Learning-Powered Electrical Brain Signals Analysis: Advancing Neurological Diagnostics
- WWW (T1)Enhancing Cross-domain Link Prediction via Evolution Process Modeling
- NeurIPS (T1)Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
- IEEE Transactions on Big DataGraphllm: Boosting graph reasoning ability of large language model
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningHandling Feature Heterogeneity with Learnable Graph Patches
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningHow to use Graph Data in the Wild to Help Graph Anomaly Detection?
- ICLR (T1)KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningLiPM: Foundation Model for Lithium-Ion Battery Analysis
- ICLR (T1)Multi-Label Node Classification with Label Influence Propagation
202421 papers
- Proceedings of the Annual Meeting of the Association of Computational LinguisticsAn Expert is Worth One Token: Synergizing Multiple Expert LLMs as Generalist via Expert Token Routing
- BHIBrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningBrant-X: A Unified Physiological Signal Alignment Framework
- WWW (T1)Can GNN be Good Adapter for LLMs?
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningCan Modifying Data Address Graph Domain Adaptation?
- Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data MiningChromosomal Structural Abnormality Diagnosis by Homologous Similarity
- NeurIPS (T1)Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
- IJCAI (T1)Disentangling Domain and General Representations for Time Series Classification
- NeurIPS (T1)DMNet: Self-comparison Driven Model for Subject-independent Seizure Detection
- IJCAI (T1)DWLR: Domain Adaptation under Label Shift for Wearable Sensor
- ICML (T1)Exploring Correlations of Self-Supervised Tasks for Graphs
- NeurIPS (T1)Extracting Training Data from Molecular Pre-trained Models
202312 papers
- AAAI (T1)(Distinguished Paper Award)
- Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAccelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds
- Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data MiningAn Answer from Data Generation Perspective!
- NeurIPS (T1)Better with Less: A Data-Centric Prespective on Pre-Training Graph Neural Networks
- NeurIPS (T1)Brant: Foundation Model for Intracranial Neural Signal
- WWW (T1)CogDL: A Comprehensive Library for Graph Deep Learning
- Proceedings of the Twenty-Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data MiningMBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals
- EMNLP (T1)MediaHG: Rethinking Eye-catchy Features in Social Media Headline Generation
- —Nature Scientific Reports (opens in a new tab)
- NeurIPS (T1)PPi: Pretraining Brain Signal Model for Patient-independent Seizure Detection
- AAAI (T1)Towards Learning to Discover Money Laundering Sub-network in Massive Transaction Network
- NeurIPS (T1)Universal Prompt Tuning for Graph Neural Networks
Where alumni went40 listed, 75% to industry
Industry 18Academia 6
Most often to
- Alibaba
- ByteDance
- Tencent
Also to
- Duke University
- HKUST
- Nanhu Academy
Apply to ZhejiangFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- Per ZJU language requirements
- Fee
- RMB 800
Not yet confirmed for this intake.
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