Jie Wen

1.0k total citations · 1 hit paper
28 papers, 557 citations indexed

About

Jie Wen is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Jie Wen has authored 28 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 12 papers in Information Systems and 10 papers in Computer Networks and Communications. Recurrent topics in Jie Wen's work include Advanced Graph Neural Networks (8 papers), Recommender Systems and Techniques (6 papers) and Caching and Content Delivery (4 papers). Jie Wen is often cited by papers focused on Advanced Graph Neural Networks (8 papers), Recommender Systems and Techniques (6 papers) and Caching and Content Delivery (4 papers). Jie Wen collaborates with scholars based in China, Australia and Malaysia. Jie Wen's co-authors include Zhixia Zhang, Zhihua Cui, Y. Lan, Jianghui Cai, Wensheng Zhang, Nan Jiang, Xingjuan Cai, Jin Li, Ximeng Liu and Di Jin and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Jie Wen

24 papers receiving 541 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.

A survey on federated learning: challenges and applications

2022 304 citations Jie Wen, Zhixia Zhang et al. International Journal of Machine Learning and Cybernetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jie Wen China	10	364	133	114	59	47	28	557
Chaoyang He United States	11	516 1.4×	106 0.8×	107 0.9×	64 1.1×	110 2.3×	22	711
Yilun Jin China	12	512 1.4×	59 0.4×	86 0.8×	58 1.0×	81 1.7×	28	701
Zuobin Xiong United States	10	395 1.1×	120 0.9×	80 0.7×	71 1.2×	137 2.9×	21	599
Hangyu Zhu China	7	682 1.9×	119 0.9×	87 0.8×	88 1.5×	107 2.3×	13	806
Francesco Cauteruccio Italy	16	257 0.7×	160 1.2×	108 0.9×	44 0.7×	71 1.5×	40	559
Y. Ding China	6	218 0.6×	77 0.6×	133 1.2×	46 0.8×	63 1.3×	13	427
Ons Aouedi France	11	425 1.2×	419 3.2×	113 1.0×	91 1.5×	46 1.0×	23	706
Virginia Smith United States	9	511 1.4×	179 1.3×	61 0.5×	103 1.7×	85 1.8×	21	652
Mohammad Ahsan Chishti India	15	147 0.4×	287 2.2×	154 1.4×	88 1.5×	82 1.7×	59	565
Jed Mills United Kingdom	7	489 1.3×	224 1.7×	123 1.1×	157 2.7×	39 0.8×	8	650

Countries citing papers authored by Jie Wen

Since Specialization

Citations

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

Fields of papers citing papers by Jie Wen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jie Wen

This figure shows the co-authorship network connecting the top 25 collaborators of Jie Wen. A scholar is included among the top collaborators of Jie Wen 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 Jie Wen. Jie Wen 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.

Wen, Jie, Qian Wang, Haiying Dong, & Zhihua Cui. (2025). Personalized Indicator Based Evolutionary Algorithm for Uncertain Constrained Many‐Objective Optimization Problem With Interval Functions. Concurrency and Computation Practice and Experience. 37(3). 1 indexed citations

2.

Cai, Jianghui, et al.. (2025). A Fairness-Aware Resource Management Model With Many-Objective Optimization in Uncertain Resource-Constrained Internet of Vehicles. IEEE Internet of Things Journal. 12(14). 26718–26729.

3.

Yang, Xikang, et al.. (2025). DS-GCG: Enhancing LLM Jailbreaks with Token Suppression and Induction Dual-Strategy. 273–278. 1 indexed citations

4.

Wen, Jie, et al.. (2024). Resource-aware multi-criteria vehicle participation for federated learning in Internet of vehicles. Information Sciences. 664. 120344–120344. 10 indexed citations

5.

Lin, Dan-Dan, et al.. (2024). PlatoD2GL: An Efficient Dynamic Deep Graph Learning System for Graph Neural Network Training on Billion-Scale Graphs. 2421–2434. 1 indexed citations

6.

Wen, Jie, et al.. (2024). RTrust: toward robust trust evaluation framework for fake news detection in online social networks. World Wide Web. 27(6).

7.

Wen, Jie, et al.. (2024). TA-Detector: A GNN-Based Anomaly Detector via Trust Relationship. ACM Transactions on Multimedia Computing Communications and Applications. 21(8). 1–21. 3 indexed citations

8.

Jiang, Nan, et al.. (2024). TPoison: Data-Poisoning Attack against GNN-Based Social Trust Model. Mathematics. 12(12). 1813–1813. 2 indexed citations

9.

Wen, Jie, et al.. (2023). A many‐objective optimization‐based local tensor factorization model for skin cancer detection. Concurrency and Computation Practice and Experience. 36(6).

10.

Zhang, Zhixia, Jie Wen, Xingjuan Cai, & Zhihua Cui. (2023). A many‐objective optimization algorithm with dual criteria and mixed distribution correction strategy. Concurrency and Computation Practice and Experience. 35(21). 1 indexed citations

11.

Cai, Jianghui, et al.. (2023). A game theory based many-objective hybrid tensor decomposition for skin cancer prediction. Expert Systems with Applications. 239. 122425–122425. 9 indexed citations

12.

Jiang, Nan, et al.. (2023). NAH: neighbor-aware attention-based heterogeneous relation network model in E-commerce recommendation. World Wide Web. 26(5). 2373–2394. 2 indexed citations

13.

Chen, Yueying, Aiping Liu, Xueyang Fu, Jie Wen, & Xun Chen. (2022). An Invertible Dynamic Graph Convolutional Network for Multi-Center ASD Classification. Frontiers in Neuroscience. 15. 828512–828512. 7 indexed citations

14.

Wen, Jie, Zhixia Zhang, Y. Lan, et al.. (2022). A survey on federated learning: challenges and applications. International Journal of Machine Learning and Cybernetics. 14(2). 513–535. 304 indexed citations breakdown →

15.

Cui, Zhihua, Jie Wen, Y. Lan, Zhixia Zhang, & Jianghui Cai. (2022). Communication-efficient federated recommendation model based on many-objective evolutionary algorithm. Expert Systems with Applications. 201. 116963–116963. 21 indexed citations

16.

Cai, Xingjuan, Y. Lan, Zhixia Zhang, et al.. (2021). A Many-Objective Optimization Based Federal Deep Generation Model for Enhancing Data Processing Capability in IoT. IEEE Transactions on Industrial Informatics. 19(1). 561–569. 40 indexed citations

17.

Zhang, Zhixia, Jie Wen, Jiangjiang Zhang, Xingjuan Cai, & Liping Xie. (2020). A Many Objective-Based Feature Selection Model for Anomaly Detection in Cloud Environment. IEEE Access. 8. 60218–60231. 29 indexed citations

18.

Bai, Fuhai, et al.. (2018). [Clinical analysis for preset double J tube in percutaneous nephrolithotripsy].. PubMed. 98(6). 454–456.

19.

Chui-yong, Zheng, et al.. (2014). Applying the ensemble artificial neural network-based hybrid data-driven model to daily total load forecasting. Neural Computing and Applications. 26(3). 603–611. 29 indexed citations

20.

Li, Ju, et al.. (2011). Rough Set Application in Customer Classification. Advanced materials research. 267. 46–49. 1 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.

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