Changjun Jiang

9.3k total citations · 1 hit paper
370 papers, 6.3k citations indexed

About

Changjun Jiang is a scholar working on Computer Networks and Communications, Information Systems and Artificial Intelligence. According to data from OpenAlex, Changjun Jiang has authored 370 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 136 papers in Computer Networks and Communications, 133 papers in Information Systems and 117 papers in Artificial Intelligence. Recurrent topics in Changjun Jiang's work include Business Process Modeling and Analysis (67 papers), Petri Nets in System Modeling (66 papers) and Service-Oriented Architecture and Web Services (56 papers). Changjun Jiang is often cited by papers focused on Business Process Modeling and Analysis (67 papers), Petri Nets in System Modeling (66 papers) and Service-Oriented Architecture and Web Services (56 papers). Changjun Jiang collaborates with scholars based in China, United States and United Kingdom. Changjun Jiang's co-authors include Guanjun Liu, MengChu Zhou, Zhijun Ding, Chungang Yan, Xiaobo Zhou, Zhenchuan Li, Maozhen Li, Dazhao Cheng, Junli Wang and Pengwei Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Physics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Changjun Jiang

347 papers receiving 6.1k citations

Hit Papers

Random forest for credit ... 2018 2026 2020 2023 2018 50 100 150 200

Author Peers

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

Author Last Decade Papers Cites
Changjun Jiang 2.3k 2.2k 2.2k 839 748 370 6.3k
Gang Sun 1.8k 0.8× 1.2k 0.6× 3.2k 1.5× 2.1k 2.4× 337 0.5× 292 6.1k
Francesco Palmieri 1.5k 0.7× 2.1k 1.0× 2.6k 1.2× 1.0k 1.2× 134 0.2× 234 5.5k
Qi Zhang 3.5k 1.5× 1.7k 0.8× 5.2k 2.4× 1.8k 2.1× 362 0.5× 475 8.9k
Haibin Zhu 1.1k 0.5× 1.8k 0.8× 972 0.4× 971 1.2× 272 0.4× 270 4.7k
Baowen Xu 4.9k 2.1× 2.4k 1.1× 2.3k 1.1× 1.0k 1.2× 130 0.2× 397 7.9k
Tharam S. Dillon 2.1k 0.9× 2.4k 1.1× 2.0k 0.9× 2.4k 2.8× 484 0.6× 430 8.2k
Kotagiri Ramamohanarao 2.9k 1.3× 3.5k 1.6× 4.0k 1.8× 797 0.9× 162 0.2× 364 9.2k
Farookh Khadeer Hussain 2.1k 0.9× 1.2k 0.5× 1.7k 0.8× 354 0.4× 355 0.5× 279 4.2k
Keke Gai 4.5k 2.0× 2.0k 0.9× 2.9k 1.3× 1.1k 1.3× 455 0.6× 189 6.8k
Vincenzo Loia 1.7k 0.7× 2.9k 1.3× 1.3k 0.6× 1.4k 1.7× 202 0.3× 347 7.3k

Countries citing papers authored by Changjun Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Changjun Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changjun Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Changjun Jiang. A scholar is included among the top collaborators of Changjun Jiang 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 Changjun Jiang. Changjun Jiang 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.
Jiang, Changjun, et al.. (2025). Domain-wise knowledge decoupling for personalized federated learning via Radon transform. Neurocomputing. 635. 130013–130013. 1 indexed citations
2.
Li, Ke, et al.. (2025). Multiscale Feature Fusion Transformer With Hybrid Attention for Insulator Defect Detection. IEEE Transactions on Instrumentation and Measurement. 74. 1–13. 1 indexed citations
3.
Yang, Fan, et al.. (2025). Meta Reinforcement Learning Based Adaptive and Interpretable Energy Storage Control Meets Dynamic Scenarios. IEEE Transactions on Sustainable Energy. 16(4). 2560–2572. 1 indexed citations
4.
Li, Zhong, et al.. (2025). Multi-View Graph-Based Hierarchical Representation Learning for Money Laundering Group Detection. IEEE Transactions on Information Forensics and Security. 20. 2035–2050. 1 indexed citations
5.
Ding, Zhijun, et al.. (2024). Risk contagion in interbank lending networks: A multi-agent-based modeling and simulation perspective. Expert Systems with Applications. 256. 124847–124847.
6.
Yan, Chungang, et al.. (2024). Graph ensemble neural network. Information Fusion. 110. 102461–102461. 7 indexed citations
7.
Wang, Junli, et al.. (2024). Adaptive Knowledge Recomposition for Personalized Federated Learning via Discrete Wavelet Transform. IEEE Internet of Things Journal. 11(21). 35610–35624.
8.
Wang, Cheng, et al.. (2024). Behavioral authentication for security and safety. SHILAP Revista de lepidopterología. 3. 2024003–2024003. 6 indexed citations
9.
Liu, Qinyuan, Zidong Wang, Hongli Dong, & Changjun Jiang. (2024). Distributed Kalman Filtering Under Two-Bitrate Periodic Coding Strategies. IEEE Transactions on Automatic Control. 69(12). 8633–8646. 2 indexed citations
10.
Wang, Junli, et al.. (2024). A recent survey on controllable text generation: A causal perspective. Fundamental Research. 5(3). 1194–1203.
11.
Hou, Jing, et al.. (2024). Spreeze: High-Throughput Parallel Reinforcement Learning Framework. IEEE Transactions on Parallel and Distributed Systems. 36(2). 282–292.
12.
Yan, Chungang, et al.. (2023). Class-homophilic-based data augmentation for improving graph neural networks. Knowledge-Based Systems. 269. 110518–110518. 5 indexed citations
13.
Lü, Fan, Guang Chen, Yinlong Liu, et al.. (2023). HRegNet: A Hierarchical Network for Efficient and Accurate Outdoor LiDAR Point Cloud Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(10). 11884–11897. 14 indexed citations
14.
Ding, Zhijun, et al.. (2022). Kubernetes-Oriented Microservice Placement With Dynamic Resource Allocation. IEEE Transactions on Cloud Computing. 11(2). 1777–1793. 35 indexed citations
15.
Chen, Guang, et al.. (2022). PSDC: A Prototype-Based Shared-Dummy Classifier Model for Open-Set Domain Adaptation. IEEE Transactions on Cybernetics. 53(11). 7353–7366. 24 indexed citations
16.
Li, Zhong, et al.. (2021). DDoS Mitigation Based on Space-Time Flow Regularities in IoV: A Feature Adaption Reinforcement Learning Approach. IEEE Transactions on Intelligent Transportation Systems. 23(3). 2262–2278. 23 indexed citations
17.
Li, Zhong, et al.. (2021). Tree-searching based trust assessment through communities in vehicular networks. Peer-to-Peer Networking and Applications. 14(4). 1854–1868.
18.
Cuypers, Dieter, Fang Chen, Quan Li, et al.. (2019). Dual-frequency liquid crystal-polymer grating for fast response optical beam steering. Smart Materials and Structures. 28(10). 105036–105036. 4 indexed citations
19.
Huang, Zhengwen, et al.. (2017). Schema Theory-Based Data Engineering in Gene Expression Programming for Big Data Analytics. IEEE Transactions on Evolutionary Computation. 22(5). 792–804. 7 indexed citations
20.
Yu, Wangyang, Chungang Yan, Zhijun Ding, Changjun Jiang, & MengChu Zhou. (2016). Analyzing E-Commerce Business Process Nets via Incidence Matrix and Reduction. IEEE Transactions on Systems Man and Cybernetics Systems. 48(1). 130–141. 28 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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