Wenhan Zhan
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- IoT and Edge/Fog Computing 14
- Caching and Content Delivery 5
- Age of Information Optimization 5
- Advanced Data Storage Technologies 3
- Opportunistic and Delay-Tolerant Networks 2
- Software-Defined Networks and 5G 2
- Information Systems top 5%
- Cloud Computing and Resource Management 5
- Computer Science Applications top 10%
- Artificial Intelligence top 10%
- Privacy-Preserving Technologies in Data 2
- Co-authors
- Geyong MinJin WangHancong DuanChunbo LuoQingxin ZhuChao WangNektarios GeorgalasJia Hu
- Journals
- IEEE Communications Magazine (1 paper)IEEE Transactions on Vehicular Technology (1 paper)IEEE Transactions on Computers (1 paper)
- Partner nations
- ChinaUnited KingdomAustralia
In The Last Decade
Wenhan Zhan
18 papers receiving 813 citations
Hit Papers
Peers
Comparison fields: 5 of 37
- Computer Networks and Communications 709
- Information Systems 248
- Computer Science Applications 40
- Computer Vision and Pattern Recognition 133
- Artificial Intelligence 155
Countries citing papers authored by Wenhan Zhan
This map shows the geographic impact of Wenhan Zhan'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 Wenhan Zhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenhan Zhan more than expected).
Fields of papers citing papers by Wenhan Zhan
This network shows the impact of papers produced by Wenhan Zhan. 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 Wenhan Zhan. The network helps show where Wenhan Zhan may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Wenhan Zhan, 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 | 2025 | 1 | |
| 2 | 2025 | 4 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 25 | |
| 6 | 2023 | 0 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 12 | |
| 11 | Dependent Task Offloading for Edge Computing based on Deep Reinforcement Learningbreakdown → | 2021 | 140 |
| 12 | Deep-Reinforcement-Learning-Based Offloading Scheduling for Vehicular Edge Computingbreakdown → | 2020 | 240 |
| 13 | 2020 | 150 | |
| 14 | 2019 | 25 | |
| 15 | 2019 | 4 | |
| 16 | 2019 | 194 | |
| 17 | 2016 | 1 | |
| 18 | 2015 | 1 | |
| 19 | 2015 | 13 | |
| 20 | 2014 | 5 |
About Wenhan Zhan
Wenhan Zhan is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition, having authored 20 papers that have together received 820 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (14 papers), Cloud Computing and Resource Management (5 papers), Caching and Content Delivery (5 papers), Age of Information Optimization (5 papers), Advanced Data Storage Technologies (3 papers), Privacy-Preserving Technologies in Data (2 papers), Opportunistic and Delay-Tolerant Networks (2 papers) and Software-Defined Networks and 5G (2 papers). The work is most often cited by research in Computer Networks and Communications (709 citations), Information Systems (248 citations) and Computer Science Applications (40 citations). Wenhan Zhan has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Geyong Min, Jin Wang, Hancong Duan, Chunbo Luo, Qingxin Zhu, Chao Wang, Nektarios Georgalas, Jia Hu, Qiang Ni and Albert Y. Zomaya. Their work appears in journals such as IEEE Communications Magazine, IEEE Transactions on Vehicular Technology and IEEE Transactions on Computers.
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.