Shigen Shen

5.3k total citations · 3 hit papers
144 papers, 3.9k citations indexed

About

Shigen Shen is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Shigen Shen has authored 144 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 83 papers in Computer Networks and Communications, 35 papers in Artificial Intelligence and 28 papers in Information Systems. Recurrent topics in Shigen Shen's work include Network Security and Intrusion Detection (32 papers), IoT and Edge/Fog Computing (22 papers) and Privacy-Preserving Technologies in Data (17 papers). Shigen Shen is often cited by papers focused on Network Security and Intrusion Detection (32 papers), IoT and Edge/Fog Computing (22 papers) and Privacy-Preserving Technologies in Data (17 papers). Shigen Shen collaborates with scholars based in China, Australia and United Kingdom. Shigen Shen's co-authors include Shui Yu, Haiping Zhou, Qiying Cao, Guowen Wu, Jian Hua Liu, Zongda Wu, Longjun Huang, Enhong Chen, Zongda Wu and Yizhou Shen and has published in prestigious journals such as Proceedings of the IEEE, Scientific Reports and Journal of Materials Chemistry A.

In The Last Decade

Shigen Shen

134 papers receiving 3.8k citations

Hit Papers

Joint Differential Game and Double Deep Q-Networks for Su... 2023 2026 2024 2025 2023 2023 2024 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shigen Shen China 38 2.0k 1.3k 842 676 464 144 3.9k
Jianhua Li China 38 2.5k 1.3× 1.6k 1.3× 1.5k 1.7× 1.1k 1.6× 307 0.7× 321 4.7k
Dechang Pi China 40 1.1k 0.5× 1.7k 1.3× 409 0.5× 449 0.7× 702 1.5× 215 4.7k
Nadra Guizani United States 38 2.2k 1.1× 1.2k 0.9× 1.4k 1.7× 1.1k 1.7× 325 0.7× 104 4.4k
Xingjuan Cai China 32 1.4k 0.7× 2.0k 1.6× 1.3k 1.5× 630 0.9× 389 0.8× 130 4.8k
Pradip Kumar Sharma United Kingdom 36 2.6k 1.3× 1.4k 1.1× 2.4k 2.9× 926 1.4× 250 0.5× 134 5.2k
Chunsheng Zhu China 37 3.1k 1.6× 1.1k 0.8× 1.1k 1.3× 1.5k 2.3× 258 0.6× 177 4.9k
Laizhong Cui China 33 1.3k 0.7× 1.6k 1.2× 785 0.9× 554 0.8× 198 0.4× 148 3.5k
Sukumar Nandi India 27 1.9k 1.0× 983 0.8× 586 0.7× 1.2k 1.7× 201 0.4× 339 3.7k
Amiya Nayak Canada 41 3.6k 1.8× 1.5k 1.1× 1.0k 1.2× 2.2k 3.3× 608 1.3× 324 5.9k
Daojing He China 41 2.8k 1.4× 1.4k 1.1× 1.5k 1.7× 838 1.2× 296 0.6× 184 4.2k

Countries citing papers authored by Shigen Shen

Since Specialization
Citations

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

Fields of papers citing papers by Shigen Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shigen Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Shigen Shen. A scholar is included among the top collaborators of Shigen Shen 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 Shigen Shen. Shigen Shen 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.
Lin, Yujun, et al.. (2025). A diversity-aware incentive mechanism for cross-silo federated learning with budget constraint. Knowledge-Based Systems. 315. 113212–113212.
2.
Shen, Shigen, et al.. (2025). RMAAC: Joint Markov Games and Robust Multiagent Actor-Critic for Explainable Malware Defense in Social IoT. IEEE Transactions on Dependable and Secure Computing. 22(6). 7091–7106. 1 indexed citations
3.
Fang, Long, et al.. (2024). Maximizing VANETs Secrecy Data Rate Using Dueling Double Deep Q-Networks. IEEE Transactions on Vehicular Technology. 74(1). 1267–1279. 1 indexed citations
4.
Shen, Yizhou, et al.. (2024). SGD3QN: Joint Stochastic Games and Dueling Double Deep Q-Networks for Defending Malware Propagation in Edge Intelligence-Enabled Internet of Things. IEEE Transactions on Information Forensics and Security. 19. 6978–6990. 15 indexed citations
5.
Shen, Yizhou, et al.. (2024). Availability Evaluation of Industrial Internet of Things Under Malware Propagation: An Extended Reliability Block Diagram Approach Based on Stochastic Games. IEEE Transactions on Reliability. 74(3). 4253–4267. 7 indexed citations
6.
Shen, Shigen, Zhengjun Gao, Guowen Wu, et al.. (2024). SAC-PP: Jointly Optimizing Privacy Protection and Computation Offloading for Mobile Edge Computing. IEEE Transactions on Network and Service Management. 21(6). 6190–6203. 10 indexed citations
7.
Qi, Lianyong, et al.. (2023). An accuracy-enhanced group recommendation approach based on DEMATEL. Pattern Recognition Letters. 167. 171–180. 14 indexed citations
8.
Feng, Sheng, Liping Zhao, Haiyan Shi, et al.. (2023). One-dimensional VGGNet for high-dimensional data. Applied Soft Computing. 135. 110035–110035. 42 indexed citations
9.
Shen, Shigen, et al.. (2023). Deep Q-network-based heuristic intrusion detection against edge-based SIoT zero-day attacks. Applied Soft Computing. 150. 111080–111080. 45 indexed citations
10.
Yu, Donghua, et al.. (2023). SR-HGN: Semantic- and Relation-Aware Heterogeneous Graph Neural Network. Expert Systems with Applications. 224. 119982–119982. 33 indexed citations
12.
Wu, Zongda, et al.. (2023). A Confusion Method for the Protection of User Topic Privacy in Chinese Keyword-based Book Retrieval. ACM Transactions on Asian and Low-Resource Language Information Processing. 22(5). 1–19. 28 indexed citations
13.
Zang, Ying, et al.. (2023). Joint dual-stream interaction and multi-scale feature extraction network for multi-spectral pedestrian detection. Applied Soft Computing. 147. 110768–110768. 5 indexed citations
14.
Zhao, Zhiwei, Liang Yu, Jiajin Huang, et al.. (2023). Boosting trace SO2adsorption and separation performance by the modulation of the SBU metal component of iron-based bimetal MOFs. Journal of Materials Chemistry A. 11(27). 14728–14737. 23 indexed citations
15.
Li, Zhao, Shigen Shen, Jian Wang, et al.. (2023). Hyperspectral Image Classification Based on Dense Pyramidal Convolution and Multi-Feature Fusion. Remote Sensing. 15(12). 2990–2990. 25 indexed citations
16.
Wu, Guowen, et al.. (2023). FedNRM: A Federal Personalized News Recommendation Model Achieving User Privacy Protection. Intelligent Automation & Soft Computing. 37(2). 1729–1751. 8 indexed citations
17.
Shen, Yizhou, Shigen Shen, Qi Li, et al.. (2022). Evolutionary privacy-preserving learning strategies for edge-based IoT data sharing schemes. Digital Communications and Networks. 9(4). 906–919. 74 indexed citations
18.
Zhang, Peiying, Yu Su, Jingjing Wang, et al.. (2022). Reinforcement Learning Assisted Bandwidth Aware Virtual Network Resource Allocation. IEEE Transactions on Network and Service Management. 19(4). 4111–4123. 24 indexed citations
19.
Wang, Tian, Yilin Zhang, Naixue Xiong, et al.. (2021). An Effective Edge-Intelligent Service Placement Technology for 5G-and-Beyond Industrial IoT. IEEE Transactions on Industrial Informatics. 18(6). 4148–4157. 30 indexed citations
20.
Hu, Keli, et al.. (2017). A novel object tracking algorithm by fusing color and depth information based on single valued neutrosophic cross-entropy. Journal of Intelligent & Fuzzy Systems. 32(3). 1775–1786. 69 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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