Shangsong Liang

2.6k total citations
98 papers, 1.6k citations indexed

About

Shangsong Liang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shangsong Liang has authored 98 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Artificial Intelligence, 48 papers in Information Systems and 27 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shangsong Liang's work include Topic Modeling (35 papers), Recommender Systems and Techniques (27 papers) and Advanced Graph Neural Networks (24 papers). Shangsong Liang is often cited by papers focused on Topic Modeling (35 papers), Recommender Systems and Techniques (27 papers) and Advanced Graph Neural Networks (24 papers). Shangsong Liang collaborates with scholars based in China, United Kingdom and United Arab Emirates. Shangsong Liang's co-authors include Maarten de Rijke, Zaiqiao Meng, Zhaochun Ren, Emine Yılmaz, Xiangliang Zhang, Evangelos Kanoulas, Fei Cai, Piji Li, Teng Xiao and Shuaiqiang Wang and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Shangsong Liang

88 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shangsong Liang China 26 1.1k 838 292 255 131 98 1.6k
Panagiotis Symeonidis Greece 23 853 0.7× 1.1k 1.3× 344 1.2× 376 1.5× 160 1.2× 68 1.8k
Alexandrin Popescul United States 13 782 0.7× 1.1k 1.4× 373 1.3× 280 1.1× 238 1.8× 19 1.6k
Ron Bekkerman United States 15 862 0.8× 467 0.6× 216 0.7× 194 0.8× 183 1.4× 35 1.3k
Zheng Chen China 20 1.8k 1.6× 798 1.0× 287 1.0× 120 0.5× 78 0.6× 63 2.2k
Lejian Liao China 20 784 0.7× 569 0.7× 271 0.9× 156 0.6× 90 0.7× 123 1.3k
Richong Zhang China 22 1.2k 1.1× 434 0.5× 236 0.8× 139 0.5× 79 0.6× 118 1.7k
Kenny Q. Zhu China 20 1.5k 1.3× 627 0.7× 243 0.8× 200 0.8× 170 1.3× 94 2.1k
Julio Gonzalo Spain 23 1.6k 1.4× 700 0.8× 212 0.7× 137 0.5× 302 2.3× 98 2.0k
Ioannis Konstas United Kingdom 15 985 0.9× 767 0.9× 259 0.9× 108 0.4× 57 0.4× 40 1.5k
Tieyun Qian China 20 1.2k 1.0× 659 0.8× 168 0.6× 86 0.3× 84 0.6× 82 1.7k

Countries citing papers authored by Shangsong Liang

Since Specialization
Citations

This map shows the geographic impact of Shangsong Liang'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 Shangsong Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shangsong Liang more than expected).

Fields of papers citing papers by Shangsong Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shangsong Liang. 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 Shangsong Liang. The network helps show where Shangsong Liang may publish in the future.

Co-authorship network of co-authors of Shangsong Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Shangsong Liang. A scholar is included among the top collaborators of Shangsong Liang 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 Shangsong Liang. Shangsong Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Li, Jiyong, et al.. (2025). L4: Mutual Learning Helps Lifelong Language Learning. 1275–1286.
3.
Liang, Shangsong, et al.. (2025). DuSEGO: Dual Second-Order Equivariant Graph Ordinary Differential Equation. ACM Transactions on Knowledge Discovery from Data. 20(1). 1–18. 1 indexed citations
4.
5.
Zhou, Chenhao, et al.. (2025). User-cooperative dynamic resource allocation for backscatter-aided wireless-powered MEC network. Scientific Reports. 15(1). 16822–16822. 1 indexed citations
6.
Huang, Feng, et al.. (2024). GAT4Rec: Sequential Recommendation with a Gated Recurrent Unit and Transformers. Mathematics. 12(14). 2189–2189. 1 indexed citations
7.
Liang, Shangsong, et al.. (2024). VAE*: A Novel Variational Autoencoder via Revisiting Positive and Negative Samples for Top- N Recommendation. ACM Transactions on Knowledge Discovery from Data. 18(9). 1–24. 10 indexed citations
8.
Li, Jiyong, et al.. (2024). Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(12). 13554–13562. 4 indexed citations
9.
Zhao, Kun, et al.. (2024). Improving human activity recognition via graph attention network with linear discriminant analysis and residual learning. Biomedical Signal Processing and Control. 100. 107053–107053. 1 indexed citations
10.
Liu, Si‐Wei, et al.. (2024). PASCL: supervised contrastive learning with perturbative augmentation for particle decay reconstruction. Machine Learning Science and Technology. 5(4). 45028–45028. 2 indexed citations
11.
Meng, Zaiqiao, et al.. (2024). Towards Deep Generative Backmapping of Coarse-Grained Molecular Systems. 1–7. 1 indexed citations
12.
Nakov, Preslav, et al.. (2024). SAFARI: Cross-lingual Bias and Factuality Detection in News Media and News Articles. 12217–12231. 1 indexed citations
13.
Liang, Shangsong, et al.. (2024). Heterogeneous biomedical entity representation learning for gene–disease association prediction. Briefings in Bioinformatics. 25(5). 3 indexed citations
14.
Lin, Qiang, et al.. (2023). HMCDA: a novel method based on the heterogeneous graph neural network and metapath for circRNA-disease associations prediction. BMC Bioinformatics. 24(1). 335–335. 7 indexed citations
15.
16.
17.
Liu, Fangyu, et al.. (2022). Revisiting Parameter-Efficient Tuning: Are We Really There Yet?. 2612–2626. 32 indexed citations
18.
Zhang, Qiang, et al.. (2021). Variational Continual Bayesian Meta-Learning. Neural Information Processing Systems. 34. 5 indexed citations
19.
Zhang, Qiang, et al.. (2021). Structure-Aware Random Fourier Kernel for Graphs. Neural Information Processing Systems. 34. 3 indexed citations
20.
Liang, Shangsong. (2014). Fusion and diversification in information retrieval. UvA-DARE (University of Amsterdam).

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

Breakdown of academic impact, for papers by Panagiotis Symeonidis Breakdown of academic impact, for papers by Alexandrin Popescul Breakdown of academic impact, for papers by Ron Bekkerman Breakdown of academic impact, for papers by Zheng Chen Breakdown of academic impact, for papers by Lejian Liao Breakdown of academic impact, for papers by Richong Zhang Breakdown of academic impact, for papers by Kenny Q. Zhu Breakdown of academic impact, for papers by Julio Gonzalo Breakdown of academic impact, for papers by Ioannis Konstas Breakdown of academic impact, for papers by Tieyun Qian
Rankless by CCL
2026