Miaojiang Chen
Impact in
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- IoT and Edge/Fog Computing
- Age of Information Optimization
- Computer Science Applications top 10%
Papers in
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- IoT and Edge/Fog Computing 10
- Age of Information Optimization 4
- Software-Defined Networks and 5G 2
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- Advanced Wireless Communication Technologies 3
- IoT Networks and Protocols 2
- Co-authors
- Anfeng Liu (10 shared papers)Tian Wang (5 shared papers)Wei Liu (5 shared papers)Shaobo Zhang (2 shared papers)Kaoru Ota (2 shared papers)Mianxiong Dong (2 shared papers)Ming Zhao (1 shared paper)Naixue Xiong (3 shared papers)
- Journals
- Computer Communications (2 papers)Expert Systems with Applications (2 papers)ACM Transactions on Sensor Networks (1 paper)Information Fusion (1 paper)IEEE Internet of Things Journal (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Miaojiang Chen
12 papers receiving 457 citations
Peers
Comparison fields: 5 of 50
- Computer Networks and Communications 307
- Computer Science Applications 26
- Information Systems 103
- Artificial Intelligence 139
- Computer Vision and Pattern Recognition 59
Countries citing papers authored by Miaojiang Chen
This map shows the geographic impact of Miaojiang 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 Miaojiang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miaojiang Chen more than expected).
Fields of papers citing papers by Miaojiang Chen
This network shows the impact of papers produced by Miaojiang 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 Miaojiang Chen. The network helps show where Miaojiang Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Miaojiang Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 94 | |
| 2 | 2021 | 88 | |
| 3 | 2021 | 71 | |
| 4 | 2021 | 42 | |
| 5 | 2023 | 36 | |
| 6 | 2022 | 35 | |
| 7 | 2021 | 33 | |
| 8 | 2022 | 29 | |
| 9 | 2023 | 23 | |
| 10 | 2022 | 11 | |
| 11 | 2024 | 6 | |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 |
About Miaojiang Chen
Miaojiang Chen is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 14 papers that have together received 469 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (10 papers), Age of Information Optimization (4 papers), Advanced Wireless Communication Technologies (3 papers), IoT Networks and Protocols (2 papers), Cloud Computing and Resource Management (2 papers), Blockchain Technology Applications and Security (2 papers), Privacy-Preserving Technologies in Data (2 papers) and Software-Defined Networks and 5G (2 papers). The work is most often cited by research in Computer Networks and Communications (307 citations), Computer Science Applications (26 citations), Information Systems (103 citations), Artificial Intelligence (139 citations) and Computer Vision and Pattern Recognition (59 citations). Miaojiang Chen has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Anfeng Liu, Tian Wang, Wei Liu, Shaobo Zhang, Kaoru Ota, Mianxiong Dong, Ming Zhao, Naixue Xiong, Yingying Ren and Houbing Song. Their work appears in journals such as Computer Communications, Expert Systems with Applications, ACM Transactions on Sensor Networks, Information Fusion and IEEE Internet of Things Journal.
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.