Zhenkun Cai
Impact in
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- Graph Theory and Algorithms
- Advanced Neural Network Applications
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Stochastic Gradient Optimization Techniques
Papers in
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- Advanced Graph Neural Networks 5
- Stochastic Gradient Optimization Techniques 3
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- Caching and Content Delivery 3
- Co-authors
- James Cheng (11 shared papers)Xiao Yan (8 shared papers)Fan Yu (2 shared papers)Yan Xiao (2 shared papers)Yuzhen Huang (3 shared papers)Jinfeng Li (1 shared paper)Boyang Li (1 shared paper)Han Yuan (1 shared paper)
- Journals
- IEEE Transactions on Parallel and Distributed Systems (2 papers)Trends in Microbiology (1 paper)Parallel Computing (1 paper)Science Advances (1 paper)Proceedings of the VLDB Endowment (1 paper)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Zhenkun Cai
16 papers receiving 286 citations
Peers
Comparison fields: 5 of 36
- Computer Vision and Pattern Recognition 154
- Artificial Intelligence 194
- Hardware and Architecture 35
- Computer Networks and Communications 94
- Information Systems 78
Countries citing papers authored by Zhenkun Cai
This map shows the geographic impact of Zhenkun Cai'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 Zhenkun Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhenkun Cai more than expected).
Fields of papers citing papers by Zhenkun Cai
This network shows the impact of papers produced by Zhenkun Cai. 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 Zhenkun Cai. The network helps show where Zhenkun Cai may publish in the future.
Co-authors
The 25 scholars most cited alongside Zhenkun Cai, 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 | 2021 | 66 | |
| 2 | 2018 | 52 | |
| 3 | 2021 | 42 | |
| 4 | 2021 | 33 | |
| 5 | 2021 | 25 | |
| 6 | 2023 | 18 | |
| 7 | 2020 | 17 | |
| 8 | 2023 | 9 | |
| 9 | 2023 | 7 | |
| 10 | 2024 | 7 | |
| 11 | 2023 | 5 | |
| 12 | 2018 | 4 | |
| 13 | 2024 | 3 | |
| 14 | 2025 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 |
About Zhenkun Cai
Zhenkun Cai is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Molecular Biology, having authored 16 papers that have together received 292 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (5 papers), Cloud Computing and Resource Management (4 papers), Recommender Systems and Techniques (3 papers), Parallel Computing and Optimization Techniques (3 papers), Advanced Neural Network Applications (3 papers), Caching and Content Delivery (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (154 citations), Artificial Intelligence (194 citations), Hardware and Architecture (35 citations), Computer Networks and Communications (94 citations) and Information Systems (78 citations). Zhenkun Cai has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include James Cheng, Xiao Yan, Fan Yu, Yan Xiao, Yuzhen Huang, Fan Yu, Jinfeng Li, Boyang Li, Han Yuan and Liu Zhi. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, Trends in Microbiology, Parallel Computing, Science Advances and Proceedings of the VLDB Endowment.
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.