Kai Lei
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- Caching and Content Delivery 43
- Cooperative Communication and Network Coding 20
- Opportunistic and Delay-Tolerant Networks 15
- Peer-to-Peer Network Technologies 11
- Artificial Intelligence top 1%
- Topic Modeling 25
- Advanced Graph Neural Networks 13
- Information Systems top 1%
- Blockchain Technology Applications and Security 12
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- Complex Network Analysis Techniques 13
- Journals
- IEEE Access (4 papers)Neural Computing and Applications (3 papers)Information Sciences (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Kai Lei
128 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 128
- Computer Networks and Communications 899
- Artificial Intelligence 939
- Information Systems 596
- Statistical and Nonlinear Physics 192
- Computer Vision and Pattern Recognition 259
Countries citing papers authored by Kai Lei
This map shows the geographic impact of Kai Lei'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 Kai Lei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Lei more than expected).
Fields of papers citing papers by Kai Lei
This network shows the impact of papers produced by Kai Lei. 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 Kai Lei. The network helps show where Kai Lei may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kai Lei, 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 | 2024 | 3 | |
| 2 | 2022 | 5 | |
| 3 | 2022 | 1 | |
| 4 | 2021 | 6 | |
| 5 | 2020 | 5 | |
| 6 | 2020 | 113 | |
| 7 | 2020 | 8 | |
| 8 | 2020 | 26 | |
| 9 | 2020 | 35 | |
| 10 | 2019 | 15 | |
| 11 | 2019 | 18 | |
| 12 | 2019 | 19 | |
| 13 | 2019 | 89 | |
| 14 | Aligning Visual Regions and Textual Concepts: Learning Fine-Grained Image Representations for Image Captioning. | 2019 | 1 |
| 15 | 2019 | 32 | |
| 16 | 2019 | 69 | |
| 17 | 2018 | 26 | |
| 18 | 2018 | 55 | |
| 19 | 2018 | 44 | |
| 20 | 2018 | 4 |
About Kai Lei
Kai Lei is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics and Health Information Management, having authored 139 papers that have together received 2.2k indexed citations. Recurring topics across this work include Caching and Content Delivery (43 papers), Topic Modeling (25 papers), Cooperative Communication and Network Coding (20 papers), Opportunistic and Delay-Tolerant Networks (15 papers), Advanced Graph Neural Networks (13 papers), Complex Network Analysis Techniques (13 papers), Blockchain Technology Applications and Security (12 papers) and Peer-to-Peer Network Technologies (11 papers). The work is most often cited by research in Computer Networks and Communications (899 citations), Artificial Intelligence (939 citations), Information Systems (596 citations), Statistical and Nonlinear Physics (192 citations) and Computer Vision and Pattern Recognition (259 citations). Kai Lei has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ying Shen, Min Yang, Bo Bai, Meng Qin, Kuai Xu, Tong Jin, Min Yang, Yaliang Li, Gong Zhang and Qichao Zhang. Their work appears in journals such as IEEE Access, Neural Computing and Applications, Information Sciences, Neurocomputing and Expert Systems with Applications.
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.