Hanghang Tong
Professor
Studies large-scale data mining and machine learning on graphs, including graph neural networks and network analysis.
Hanghang Tong's lab at UIUC works on graph mining & networks, data management & big data and graph learning. 123 papers since 2023, 92 at top venues, mostly KDD and ICLR. 14 PhD students. 28 alumni. Applications close .
At a glance
- papers, 2023–2026
- 32/ year
- at T1 venues
- 75%
- PhD students
- 14
- MS students
- 0
- alumni listed
- 28
Papers by yearfrom DBLP, 2023–2026
- 24 papers2026 · T1 18 · collecting
- 30 papers2025 · T1 26
- 38 papers2024 · T1 27
- 31 papers2023 · T1 21
T1 venuesOtherVenues: KDD, ICLR, CIKM, WWW, NeurIPS
Research focuspaper titles that use each topic's words
- Graph learning58 papers
- Graph mining & networks49 papers
- Data management & big data9 papers
- studies large-scale0 papers
- large-scale data0 papers
Paper list
From DBLP.
202624 papers
- KDD (T1)A Hands-on Tutorial for Diffusion Language Models with dLLM (opens in a new tab)
- Trans. Mach. Learn. Res.A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents (opens in a new tab)
- KDD (T1)Certified Defense on the Fairness of Graph Neural Networks (opens in a new tab)
- ICLR (T1)Continual Low-Rank Adapters for LLM-based Generative Recommender Systems (opens in a new tab)
- ACL (T1)dLLM: Simple Diffusion Language Modeling (opens in a new tab)
- Findings of ACLDo VLMs Have a Moral Backbone? A Study on the Fragile Morality of Vision-Language Models (opens in a new tab)
- KDD (T1)DuET: Dual-View Tensor-to-Topology Spectral Adapter for Enhancing Sparse Tensor Factorization (opens in a new tab)
- WWW (T1)FeDecider: An LLM-Based Framework for Federated Cross-Domain Recommendation (opens in a new tab)
- KDD (T1)Graph Diffusion History Reconstruction via Feasibility-Aware Markov Chain Monte Carlo Estimation (opens in a new tab)
- ICLR (T1)Graph homophily booster: Reimagining the role of discrete features in heterophilic graph learning (opens in a new tab)
- Findings of EACLHarnessing Consistency for Robust Test-Time LLM Ensemble (opens in a new tab)
- Findings of EACLHow to Make LMs Strong Node Classifiers? (opens in a new tab)
202530 papers
- IEEE Big DataAdversarial Bias: Data Poisoning Attacks on Fairness (opens in a new tab)
- ICLR (T1)Ask, and it shall be given: On the Turing completeness of prompting (opens in a new tab)
- ICML (T1)Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting (opens in a new tab)
- CIKM (T1)ClimateBench-M: A Multi-Modal Climate Data Benchmark with a Simple Generative Method (opens in a new tab)
- NeurIPS (T1)CLIMB: Class-imbalanced Learning Benchmark on Tabular Data (opens in a new tab)
- CIKM (T1)Continual Recommender Systems (opens in a new tab)
- TKDE (T1)Deep Graph Anomaly Detection: A Survey and New Perspectives (opens in a new tab)
- SIGIR (T1)Embracing Plasticity: Balancing Stability and Plasticity in Continual Recommender Systems (opens in a new tab)
- BMC Bioinform.Enhancing biomedical named entity recognition with parallel boundary detection and category classification (opens in a new tab)
- TKDE (T1)Enhancing Hyperedge Prediction With Context-Aware Self-Supervised Learning (opens in a new tab)
- CIKM (T1)Few-Shot Knowledge Graph Completion via Transfer Knowledge from Similar Tasks (opens in a new tab)
- CIKM (T1)Fine-Grained Graph Rationalization (opens in a new tab)
202438 papers
- KDD (T1)AIM: Attributing, Interpreting, Mitigating Data Unfairness (opens in a new tab)
- ACM Trans. Knowl. Discov. DataArieL: Adversarial Graph Contrastive Learning (opens in a new tab)
- Commun. ACMArtificial Intelligence, Social Responsibility, and the Roles of the University (opens in a new tab)
- NeurIPS (T1)BackTime: Backdoor Attacks on Multivariate Time Series Forecasting (opens in a new tab)
- IEEE Trans. Vis. Comput. Graph.Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-Link Diagrams (opens in a new tab)
- ICML (T1)Class-Imbalanced Graph Learning without Class Rebalancing (opens in a new tab)
- Findings of ACLConversational Question Answering with Language Models Generated Reformulations over Knowledge Graph (opens in a new tab)
- ICLR (T1)Deceptive Fairness Attacks on Graphs via Meta Learning (opens in a new tab)
- NeurIPS (T1)Discrete-state Continuous-time Diffusion for Graph Generation (opens in a new tab)
- KDD (T1)Distributional Network of Networks for Modeling Data Heterogeneity (opens in a new tab)
- WWW (T1)Ensuring User-side Fairness in Dynamic Recommender Systems (opens in a new tab)
- ICDE (T1)Fairgen: Towards Fair Graph Generation (opens in a new tab)
202331 papers
- TKDE (T1)Adversarial Attacks on Multi-Network Mining: Problem Definition and Fast Solutions (opens in a new tab)
- LoGBeMap: Balanced Message Passing for Fair Graph Neural Network (opens in a new tab)
- TKDE (T1)BL-GAN: Semi-Supervised Bug Localization via Generative Adversarial Network (opens in a new tab)
- SDMConcept Discovery for Fast Adaptation (opens in a new tab)
- TKDE (T1)Decoupled Representation Learning for Attributed Networks (opens in a new tab)
- ICLR (T1)Do We Really Need Complicated Model Architectures For Temporal Networks? (opens in a new tab)
- Knowl. Inf. Syst.Embedding text-rich graph neural networks with sequence and topical semantic structures (opens in a new tab)
- NeurIPS (T1)From Trainable Negative Depth to Edge Heterophily in Graphs (opens in a new tab)
- ICML (T1)Generative Graph Dictionary Learning (opens in a new tab)
- CIKM (T1)Geometric Matrix Completion via Sylvester Multi-Graph Neural Network (opens in a new tab)
- TKDE (T1)Graph Vulnerability and Robustness: A Survey (opens in a new tab)
- ALTImproved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs (opens in a new tab)
Where alumni went28 listed
Apply to UIUCFall 2027
UIUC Siebel Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL iBT / IELTS
- Fee
- USD 90
Not yet confirmed for this intake.
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