2026 Shu Wu: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	39	9610	9334	1214	1208	188	8370

Overview

Shu Wu is affiliated with the Chinese Academy of Sciences in China and has an extensive publication record primarily in the field of computer science, with a focus on artificial intelligence and related disciplines.

Their research spans multiple subfields, including artificial intelligence, information systems, computer vision and pattern recognition, sociology and political science, and statistical and nonlinear physics.

Shu Wu's contributions cover a variety of main topics such as:

Advanced Graph Neural Networks
Topic Modeling
Recommender Systems and Techniques
Misinformation and Its Impacts
Domain Adaptation and Few-Shot Learning
Complex Network Analysis Techniques
Natural Language Processing Techniques

Notable recent papers by Shu Wu include:

Deep Graph Contrastive Representation Learning, 2020, arXiv (Cornell University)
Dynamic Graph Neural Networks for Sequential Recommendation, 2022, IEEE Transactions on Knowledge and Data Engineering
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation, 2022, IEEE Transactions on Knowledge and Data Engineering
Evidence-aware Fake News Detection with Graph Neural Networks, 2022, Proceedings of the ACM Web Conference 2022
Independence Promoted Graph Disentangled Networks, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Their frequent coauthors include Liang Wang, Qiang Liu, Yanqiao Zhu, Zeyu Cui, and Mengqi Zhang.

Shu Wu's work has been published in several venues repeatedly, with a particular focus on:

arXiv (Cornell University)
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the AAAI Conference on Artificial Intelligence
Pattern Recognition
Machine Intelligence Research

With over 200 publications, Shu Wu's research integrates areas such as graph neural networks, recommendation systems, misinformation detection, and computational techniques for complex networks and domain adaptation. Their scholarly output contributes to evolving methods and understanding within artificial intelligence and computer science broadly.

Best Publications

Session-Based Recommendation with Graph Neural Networks

Shu Wu;Yuyuan Tang;Yanqiao Zhu;Liang Wang

2545
Citations
Predicting the next location: a recurrent model with spatial and temporal contexts

Qiang Liu;Shu Wu;Liang Wang;Tieniu Tan

1006
Citations
Graph Contrastive Learning with Adaptive Augmentation

Yanqiao Zhu;Yichen Xu;Feng Yu;Qiang Liu

949
Citations
A Dynamic Recurrent Model for Next Basket Recommendation

Feng Yu;Qiang Liu;Shu Wu;Liang Wang

513
Citations
A convolutional approach for misinformation identification

Feng Yu;Qiang Liu;Shu Wu;Liang Wang

465
Citations
Deep Graph Contrastive Representation Learning.

Yanqiao Zhu;Yichen Xu;Feng Yu;Qiang Liu

443
Citations
Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks

Yufeng Zhang;Xueli Yu;Zeyu Cui;Shu Wu

304
Citations
A Comprehensive Survey on Cross-modal Retrieval

Kaiye Wang;Qiyue Yin;Wei Wang;Shu Wu

275
Citations
Mining Latent Structures for Multimedia Recommendation

Jinghao Zhang;Yanqiao Zhu;Qiang Liu;Shu Wu

253
Citations
Mining Latent Structures for Multimedia Recommendation

Jinghao Zhang;Yanqiao Zhu;Qiang Liu;Shu Wu

250
Citations
Context-Aware Sequential Recommendation

Qiang Liu;Shu Wu;Diyi Wang;Zhaokang Li

208
Citations
Dynamic Graph Neural Networks for Sequential Recommendation.

Mengqi Zhang;Shu Wu;Xueli Yu;Liang Wang

195
Citations
TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation

Feng Yu;Yanqiao Zhu;Qiang Liu;Shu Wu

194
Citations
Information-Theoretic Outlier Detection for Large-Scale Categorical Data

Shu Wu;Shengrui Wang

179
Citations
MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation

Qiang Cui;Shu Wu;Qiang Liu;Wen Zhong

173
Citations
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

Zekun Li;Zeyu Cui;Shu Wu;Xiaoyu Zhang

167
Citations
Graph Contrastive Learning with Adaptive Augmentation

Yanqiao Zhu;Yichen Xu;Feng Yu;Qiang Liu

165
Citations
DeepStyle: Learning User Preferences for Visual Recommendation

Qiang Liu;Shu Wu;Liang Wang

163
Citations
A Convolutional Click Prediction Model

Qiang Liu;Feng Yu;Shu Wu;Liang Wang

152
Citations
Multi-view clustering via pairwise sparse subspace representation

Qiyue Yin;Shu Wu;Ran He;Liang Wang

142
Citations
Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification.

Fenyu Hu;Yanqiao Zhu;Shu Wu;Liang Wang

128
Citations
Latent Structure Mining With Contrastive Modality Fusion for Multimedia Recommendation

Unknown

120
Citations
Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks

Zeyu Cui;Zekun Li;Shu Wu;Xiao-Yu Zhang

103
Citations
Unified subspace learning for incomplete and unlabeled multi-view data

Qiyue Yin;Shu Wu;Liang Wang

98
Citations
Multi-Behavioral Sequential Prediction with Recurrent Log-Bilinear Model

Qiang Liu;Shu Wu;Liang Wang

96
Citations
Dynamic Graph Collaborative Filtering

Xiaohan Li;Mengqi Zhang;Shu Wu;Zheng Liu

84
Citations
Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction

Zekun Li;Zeyu Cui;Shu Wu;Xiaoyu Zhang

61
Citations

Frequent Co-Authors

Liang Wang Chinese Academy of Sciences

Tieniu Tan Chinese Academy of Sciences

Daqing Zhang Peking University

Yongzhen Huang Chinese Academy of Sciences

Ke Xu Beihang University

Shuhui Wang Chinese Academy of Sciences

Ran He Chinese Academy of Sciences

Xing Xie Microsoft Research Asia (China)

Philip S. Yu University of Illinois at Chicago

He Qing Huang Chinese Academy of Sciences

External Links

Personal website of Shu Wu

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