Shu Wu

8.3k total citations · 4 hit papers
105 papers, 3.7k citations indexed

About

Shu Wu is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shu Wu has authored 105 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 46 papers in Information Systems and 25 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shu Wu's work include Recommender Systems and Techniques (33 papers), Advanced Graph Neural Networks (30 papers) and Topic Modeling (27 papers). Shu Wu is often cited by papers focused on Recommender Systems and Techniques (33 papers), Advanced Graph Neural Networks (30 papers) and Topic Modeling (27 papers). Shu Wu collaborates with scholars based in China, United States and Canada. Shu Wu's co-authors include Liang Wang, Tieniu Tan, Qiang Liu, Qiang Liu, Qiyue Yin, Yu Feng, Feng Yu, Qiang Liu, Qiang Liu and Xueli Yu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and ACM Transactions on Graphics.

In The Last Decade

Shu Wu

100 papers receiving 3.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts

2016 633 citations Qiang Liu, Shu Wu et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →
A Dynamic Recurrent Model for Next Basket Recommendation

2016 324 citations Qiang Liu, Shu Wu et al. profile →
A Convolutional Approach for Misinformation Identification

2017 314 citations Qiang Liu, Shu Wu et al. profile →
Dynamic Graph Neural Networks for Sequential Recommendation

2022 141 citations Mengqi Zhang, Shu Wu et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shu Wu China	28	2.0k	1.9k	1.0k	578	575	105	3.7k
Fuzhen Zhuang China	31	2.9k 1.5×	2.1k 1.1×	843 0.8×	323 0.6×	411 0.7×	118	4.6k
Defu Lian China	33	2.7k 1.3×	2.9k 1.5×	978 0.9×	172 0.3×	1.1k 1.8×	168	4.8k
Xueming Qian China	35	1.4k 0.7×	1.3k 0.7×	2.7k 2.6×	253 0.4×	463 0.8×	220	4.7k
Yong Ge United States	28	1.1k 0.5×	1.4k 0.7×	423 0.4×	213 0.4×	997 1.7×	80	2.8k
Chao Huang China	34	2.8k 1.4×	2.0k 1.1×	684 0.7×	119 0.2×	447 0.8×	122	4.1k
Zhoujun Li China	40	3.5k 1.7×	1.3k 0.7×	1.1k 1.1×	219 0.4×	168 0.3×	338	5.2k
Yaliang Li United States	33	3.2k 1.6×	1.3k 0.7×	426 0.4×	355 0.6×	307 0.5×	144	4.3k
Vincent W. Zheng Singapore	31	2.7k 1.4×	1.3k 0.7×	1.1k 1.0×	195 0.3×	1.2k 2.1×	79	5.1k
Nicholas Jing Yuan China	34	2.1k 1.0×	1.7k 0.9×	812 0.8×	180 0.3×	1.5k 2.7×	80	4.7k
Hao Peng China	34	2.9k 1.5×	1.0k 0.5×	544 0.5×	190 0.3×	517 0.9×	177	5.1k

Countries citing papers authored by Shu Wu

Since Specialization

Citations

This map shows the geographic impact of Shu Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shu Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shu Wu more than expected).

Fields of papers citing papers by Shu Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shu Wu. The network helps show where Shu Wu may publish in the future.

Co-authorship network of co-authors of Shu Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shu Wu. A scholar is included among the top collaborators of Shu Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shu Wu. Shu Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Li, Tao, Youliang Zhang, Shu Wu, et al.. (2025). Increasing collagen synthesis in fibroblasts: The roles of PCL microspheres and the SAMD11–PLOD1 axis in skin rejuvenation. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1872(4). 119931–119931. 1 indexed citations

2.

Zhao, Tong, et al.. (2025). Generate First, Then Sample: Enhancing Fake News Detection with LLM-Augmented Reinforced Sampling. 24276–24290.

3.

Liu, Qiang, Xinlong Chen, Bowen Song, et al.. (2025). Attention-guided Self-reflection for Zero-shot Hallucination Detection in Large Language Models. 21016–21032.

4.

Wu, Shu, et al.. (2025). GraphFM: Graph Factorization Machines for Feature Interaction Modelling. 22(2). 239–253. 2 indexed citations

5.

Li, Qiudan, et al.. (2025). A Self-Supervised Adaptive Tuning Approach for Out-of-Distribution Social Media Bot Detection. 1312–1315.

6.

Zou, Ying, Haoxian Zhou, Tao Li, et al.. (2025). A Feedback Loop Driven by H4K12 Lactylation and HDAC3 in Macrophages Regulates Lactate‐Induced Collagen Synthesis in Fibroblasts Via the TGF‐β Signaling. Advanced Science. 12(13). e2411408–e2411408. 6 indexed citations

7.

Zhang, Mengqi, et al.. (2024). MetaTKG++: Learning evolving factor enhanced meta-knowledge for temporal knowledge graph reasoning. Pattern Recognition. 155. 110629–110629. 3 indexed citations

8.

Zhao, Tong, et al.. (2024). MPE3: Learning meta-prompt with entity-enhanced semantics for few-shot named entity recognition. Neurocomputing. 620. 129031–129031. 1 indexed citations

9.

Wei, Yifan, et al.. (2024). EX-FEVER: A Dataset for Multi-hop Explainable Fact Verification. 9340–9353.

10.

Zou, Ying, Tao Li, Shu Wu, et al.. (2024). Lactate triggers KAT8-mediated LTBP1 lactylation at lysine 752 to promote skin rejuvenation by inducing collagen synthesis in fibroblasts. International Journal of Biological Macromolecules. 277(Pt 3). 134482–134482. 22 indexed citations

11.

Wu, Shu, et al.. (2024). Heterogeneous Graph Reasoning for Fact Checking over Texts and Tables. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 100–108. 1 indexed citations

12.

Liu, Qiang, et al.. (2024). Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection. 4150–4159. 4 indexed citations

13.

Guo, Weiyu, Zhijiang Yang, Shu Wu, Xiuli Wang, & Chen Fu. (2023). Explainable enterprise credit rating using deep feature crossing. Expert Systems with Applications. 220. 119704–119704. 2 indexed citations

14.

Zhu, Yanqiao, Yichen Xu, Feng Yu, Qiang Liu, & Shu Wu. (2023). Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining. ACM Transactions on Intelligent Systems and Technology. 14(5). 1–21. 2 indexed citations

15.

Liu, Qiang, et al.. (2023). Learning Latent Relations for Temporal Knowledge Graph Reasoning. 12617–12631. 17 indexed citations

16.

Liu, Qiang, et al.. (2023). Counterfactual Debiasing for Fact Verification. 6777–6789. 16 indexed citations

17.

Liu, Qiang, et al.. (2022). MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning. 7230–7240. 7 indexed citations

18.

Zhang, Aiqing, et al.. (2022). Blockchain-based multi-hop permission delegation scheme with controllable delegation depth for electronic health record sharing. SHILAP Revista de lepidopterología. 2(4). 100084–100084. 6 indexed citations

19.

Zhu, Yanqiao, et al.. (2019). Semi-supervised Node Classification via Hierarchical Graph Convolutional Networks. arXiv (Cornell University). 3 indexed citations

20.

Cui, Qiang, et al.. (2016). A Visual and Textual Recurrent Neural Network for Sequential Prediction.. arXiv (Cornell University). 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact