Bing Chen

5.6k total citations · 2 hit papers
258 papers, 3.7k citations indexed

About

Bing Chen is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Bing Chen has authored 258 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Computer Networks and Communications, 73 papers in Artificial Intelligence and 73 papers in Electrical and Electronic Engineering. Recurrent topics in Bing Chen's work include Privacy-Preserving Technologies in Data (33 papers), Cryptography and Data Security (20 papers) and Adversarial Robustness in Machine Learning (15 papers). Bing Chen is often cited by papers focused on Privacy-Preserving Technologies in Data (33 papers), Cryptography and Data Security (20 papers) and Adversarial Robustness in Machine Learning (15 papers). Bing Chen collaborates with scholars based in China, United States and Australia. Bing Chen's co-authors include Jiale Zhang, Feng Hu, Yanchao Zhao, Kun Zhu, Xiang Cheng, J.K. Tugnait, Shui Yu, Annie S. Wu, Kien A. Hua and Gary S. Stein and has published in prestigious journals such as Scientific Reports, Automatica and IEEE Communications Surveys & Tutorials.

In The Last Decade

Bing Chen

227 papers receiving 3.6k citations

Hit Papers

Data Security and Privacy... 2018 2026 2020 2023 2018 2022 100 200 300
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.

  1. Data Security and Privacy-Preserving in Edge Computing Paradigm: Survey and Open Issues
    2018 330 citations Jiale Zhang, Bing Chen et al. IEEE Access profile →
  2. Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
    2022 136 citations Kun Zhu, Bing Chen et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Bing Chen 1.4k 1.4k 1.1k 610 418 258 3.7k
Ruchuan Wang 760 0.6× 2.0k 1.4× 1.6k 1.5× 582 1.0× 255 0.6× 369 4.1k
Yang Zhang 1.6k 1.1× 2.4k 1.7× 1.2k 1.2× 1.1k 1.8× 344 0.8× 248 5.3k
Zhetao Li 1.1k 0.8× 2.2k 1.6× 1.5k 1.5× 1.3k 2.1× 285 0.7× 194 4.5k
Qiao Yan 887 0.6× 2.0k 1.5× 924 0.9× 535 0.9× 183 0.4× 85 3.3k
Minglu Li 811 0.6× 1.3k 1.0× 1.6k 1.5× 952 1.6× 206 0.5× 198 4.0k
Yue‐Jiao Gong 2.2k 1.6× 870 0.6× 586 0.6× 593 1.0× 411 1.0× 140 4.5k
Kai Liu 722 0.5× 1.7k 1.3× 2.0k 1.9× 314 0.5× 533 1.3× 246 3.9k
Miao Pan 1.5k 1.1× 2.6k 1.9× 3.1k 3.0× 605 1.0× 401 1.0× 348 6.1k
Chi Zhang 1.3k 0.9× 1.9k 1.4× 1.3k 1.3× 773 1.3× 116 0.3× 237 3.8k
Lei Wang 796 0.6× 1.8k 1.3× 1.9k 1.8× 609 1.0× 198 0.5× 281 3.9k

Countries citing papers authored by Bing Chen

Since Specialization
Citations

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

Fields of papers citing papers by Bing Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Chen. A scholar is included among the top collaborators of Bing Chen 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 Bing Chen. Bing Chen 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.
Qian, Zhenghua, et al.. (2025). Collision Avoidance Control for Autonomous Driving With Multiple Dynamic Obstacles in IoV: A Prediction-Enhanced APF-Based Approach. IEEE Internet of Things Journal. 12(13). 24968–24984. 1 indexed citations
3.
Chen, Bing, et al.. (2025). Multi-Party Reversible Data Hiding in Ciphertext Binary Images Based on Visual Cryptography. IEEE Signal Processing Letters. 32. 1560–1564.
4.
Zhang, Yuxuan, et al.. (2024). CooPercept: Cooperative Perception for 3D Object Detection of Autonomous Vehicles. Drones. 8(6). 228–228. 3 indexed citations
5.
Feng, Bingwen, et al.. (2024). Moiré pattern generation-based image steganography. Journal of Information Security and Applications. 82. 103753–103753. 1 indexed citations
6.
Chen, Bing, et al.. (2024). MoDID: Decentralized Identity Management for Multiple Owners. 2022–2027. 3 indexed citations
7.
Zhang, Jiale, et al.. (2023). ADFL: Defending backdoor attacks in federated learning via adversarial distillation. Computers & Security. 132. 103366–103366. 26 indexed citations
8.
Huang, Jiawei, et al.. (2023). SAPPX: Securing COTS Binaries with Automatic Program Partitioning for Intel SGX. 148–159. 1 indexed citations
9.
Shi, You, et al.. (2022). Closed-Loop Control of Edge-Cloud Collaboration Enabled IIoT: An Online Optimization Approach. ICC 2022 - IEEE International Conference on Communications. 5682–5687. 4 indexed citations
10.
Zhang, Jiale, et al.. (2022). VPFL: A verifiable privacy-preserving federated learning scheme for edge computing systems. Digital Communications and Networks. 9(4). 981–989. 42 indexed citations
11.
Chang, Xiangmao, et al.. (2022). Measurement-Based Optimization of Cell Selection in NB-IoT Networks. ACM Transactions on Sensor Networks. 18(4). 1–19. 1 indexed citations
12.
Chang, Xiangmao, et al.. (2021). Optimizing NB-IoT Power Consumption via Adaptive Radio Access. IEEE Internet of Things Journal. 9(6). 4693–4703. 6 indexed citations
13.
Shen, Chen, et al.. (2021). Machine learning based anomaly detection and diagnosis method of spinning equipment driven by spectrogram data. Journal of the Textile Institute. 113(10). 2090–2099. 1 indexed citations
14.
Yang, Xingyu, et al.. (2021). Proof of Engagement: A Flexible Blockchain Consensus Mechanism. Wireless Communications and Mobile Computing. 2021(1). 4 indexed citations
15.
Zhai, Xiangping, Xin Liu, Chunsheng Zhu, Kun Zhu, & Bing Chen. (2019). Fast Admission Control and Power Optimization With Adaptive Rates for Communication Fairness in Wireless Networks. IEEE Transactions on Mobile Computing. 20(3). 1017–1026. 3 indexed citations
16.
Chen, Xiaohong, et al.. (2018). A Novel Simulation Model for Nonstationary Rice Fading Channels. Wireless Communications and Mobile Computing. 2018(1). 10 indexed citations
17.
Zhai, Xiangping, et al.. (2018). Truthful Double Auction for Joint Internet of Energy and Profit Optimization in Cognitive Radio Networks. IEEE Access. 6. 23180–23190. 16 indexed citations
18.
Zhai, Xiangping, et al.. (2018). Energy Efficiency of Access Control With Rate Constraints in Cognitive Radio Networks. IEEE Access. 6. 36354–36363. 3 indexed citations
19.
Chen, Bing, et al.. (2012). Radial Basis Function Interpolation in Moving Mesh Technique. Jisuan wuli. 29(2). 191–197. 1 indexed citations
20.
Chen, Bing. (2012). Memory-optimized RFC Packet Classification Algorithm Merge_RFC. Journal of Chinese Computer Systems. 2 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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