Kai Lei

3.6k citations
163 papers · 2.6k · h-index 29

Impact in

Papers in

Kai Lei

149 papers receiving 2.5k citations

Peers

Kai Lei
Comparison fields: 5 of 129
  • Computer Networks and Communications 985
  • Artificial Intelligence 1.2k
  • Information Systems 712
  • Statistical and Nonlinear Physics 224
  • Computer Vision and Pattern Recognition 308
Replace Mohsen Kahani with:
Mohsen Kahani Iran
Domenico Ursino Italy
Jun Zhou China
Jianxin Li China
Paolo Trunfio Italy
Fei Hao China
Santanu Kumar Rath India
Xianghan Zheng China
Gillian Dobbie New Zealand
Kai Lei relative to Mohsen Kahani Iran Mohsen Kahani's profile →
Citations per field
00.5×1.5×2.2×
Mohsen Kahani · 1×
Citations per year

Countries citing papers authored by Kai Lei

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Kai Lei Line = papers co-authored together Kai Lei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 163 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020150
2 2019141
3 2020118
4 2018106
5 201898
6 201994
7 201975
8 201475
9 201863
10 201862
11 201758
12 201957
13 201457
14 201556
15 201749
16 201848
17 201844
18 201941
19 201841
20 202038

About Kai Lei

Kai Lei is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 163 papers that have together received 2.6k indexed citations. Recurring topics across this work include Caching and Content Delivery (45 papers), Topic Modeling (32 papers), Cooperative Communication and Network Coding (20 papers), Complex Network Analysis Techniques (16 papers), Opportunistic and Delay-Tolerant Networks (15 papers), Blockchain Technology Applications and Security (14 papers), Advanced Graph Neural Networks (13 papers) and Advanced Text Analysis Techniques (13 papers). The work is most often cited by research in Computer Networks and Communications (985 citations), Artificial Intelligence (1.2k citations), Information Systems (712 citations), Statistical and Nonlinear Physics (224 citations) and Computer Vision and Pattern Recognition (308 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, Yaliang Li, Zhuyun Qi, Min Yang and Gong Zhang. Their work appears in journals such as IEEE Access, Neural Computing and Applications, Expert Systems with Applications, Journal of Biomedical Informatics 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.

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