Jiejun Hu
Impact in
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- Mobile Crowdsensing and Crowdsourcing
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- IoT and Edge/Fog Computing
- Software-Defined Networks and 5G
Papers in
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- IoT and Edge/Fog Computing 8
- Caching and Content Delivery 3
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- Blockchain Technology Applications and Security 5
- Co-authors
- Kun Yang (4 shared papers)Kezhi Wang (2 shared papers)Liang Hu (8 shared papers)Kai Zhang (1 shared paper)Feng Wang (6 shared papers)Kuo Zhao (6 shared papers)Martin J. Reed (5 shared papers)Nikolaos Thomos (4 shared papers)
- Journals
- Applied Surface Science (3 papers)Multimedia Tools and Applications (2 papers)IEEE Transactions on Services Computing (2 papers)Soft Computing (2 papers)Information Sciences (1 paper)
- Partner nations
- ChinaUnited KingdomGermany
In The Last Decade
Jiejun Hu
28 papers receiving 463 citations
Peers
Comparison fields: 5 of 67
- Computer Science Applications 56
- Computer Networks and Communications 153
- Ceramics and Composites 34
- Information Systems 98
- Transportation 27
Countries citing papers authored by Jiejun Hu
This map shows the geographic impact of Jiejun Hu'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 Jiejun Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiejun Hu more than expected).
Fields of papers citing papers by Jiejun Hu
This network shows the impact of papers produced by Jiejun Hu. 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 Jiejun Hu. The network helps show where Jiejun Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiejun Hu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 73 | |
| 2 | 2012 | 51 | |
| 3 | 2005 | 42 | |
| 4 | 2020 | 38 | |
| 5 | 2006 | 37 | |
| 6 | 2016 | 33 | |
| 7 | 2011 | 27 | |
| 8 | 2017 | 24 | |
| 9 | 2015 | 21 | |
| 10 | 2015 | 19 | |
| 11 | 2021 | 16 | |
| 12 | 2015 | 15 | |
| 13 | 2000 | 13 | |
| 14 | 2017 | 13 | |
| 15 | 2010 | 12 | |
| 16 | 2018 | 10 | |
| 17 | 2018 | 5 | |
| 18 | 2020 | 4 | |
| 19 | 2024 | 4 | |
| 20 | 2015 | 3 |
About Jiejun Hu
Jiejun Hu is a scholar working on Computer Networks and Communications, Information Systems, Mechanical Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 28 papers that have together received 474 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (8 papers), Blockchain Technology Applications and Security (5 papers), Human Mobility and Location-Based Analysis (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Caching and Content Delivery (3 papers), Context-Aware Activity Recognition Systems (2 papers), Spaceflight effects on biology (2 papers) and Additive Manufacturing Materials and Processes (2 papers). The work is most often cited by research in Computer Science Applications (56 citations), Computer Networks and Communications (153 citations), Ceramics and Composites (34 citations), Information Systems (98 citations) and Transportation (27 citations). Jiejun Hu has collaborated with scholars based in China, United Kingdom and Germany. Frequent co-authors include Kun Yang, Kezhi Wang, Liang Hu, Kai Zhang, Feng Wang, Kuo Zhao, Martin J. Reed, Nikolaos Thomos, Jin Zhou and Xiaomin Han. Their work appears in journals such as Applied Surface Science, Multimedia Tools and Applications, IEEE Transactions on Services Computing, Soft Computing and Information Sciences.
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.