Kaige Qu

936 citations
28 papers · 632 · 1 hit paper · h-index 10

Impact in

Papers in

Kaige Qu

23 papers receiving 627 citations

Kaige Qu's Hit Papers

Split Learning Over Wireless Networks: Parallel Design and Resource Management 2023 · 160 citations
1600+1+2Years since publication50100150

Peers

Kaige Qu
Comparison fields: 5 of 44
  • Computer Networks and Communications 397
  • Artificial Intelligence 164
  • Computer Science Applications 25
  • Electrical and Electronic Engineering 256
  • Information Systems 65
Replace Jaewook Lee with:
Jaewook Lee South Korea
Yiqin Deng China
Zoubeir Mlika Canada
Abdullatif Albaseer Qatar
Zhicai Zhang China
Aneta Vulgarakis Feljan Sweden
Haodong Lu China
Hani Sami Lebanon
Mai Le South Korea
Hyame Assem Alameddine Canada
Kaige Qu relative to Jaewook Lee South Korea Jaewook Lee's profile →
Citations per field
00.5×1.5×
Jaewook Lee · 1×
Citations per year

Countries citing papers authored by Kaige Qu

Since Specialization
Citations

This map shows the geographic impact of Kaige Qu'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 Kaige Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaige Qu more than expected).

Fields of papers citing papers by Kaige Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kaige Qu. 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 Kaige Qu. The network helps show where Kaige Qu may publish in the future.

Co-authors

The 25 scholars most cited alongside Kaige Qu, 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 Kaige Qu Line = papers co-authored together Kaige Qu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Split Learning Over Wireless Networks: Parallel Design and Resource Management
Hit paper breakdown →
2023160
2 2018114
3 2021103
4 202077
5 202037
6 202432
7 202025
8 202315
9 202315
10 202114
11 20156
12 20196
13 20244
14 20224
15 20194
16 20243
17 20243
18 20153
19 20232
20 20242

About Kaige Qu

Kaige Qu is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 28 papers that have together received 632 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (8 papers), Vehicular Ad Hoc Networks (VANETs) (7 papers), Software-Defined Networks and 5G (7 papers), Advanced MIMO Systems Optimization (4 papers), Advanced Optical Network Technologies (3 papers), Network Traffic and Congestion Control (3 papers), Privacy-Preserving Technologies in Data (3 papers) and UAV Applications and Optimization (3 papers). The work is most often cited by research in Computer Networks and Communications (397 citations), Artificial Intelligence (164 citations), Computer Science Applications (25 citations), Electrical and Electronic Engineering (256 citations) and Information Systems (65 citations). Kaige Qu has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Weihua Zhuang, Xuemin Shen, Qiang Ye, Xu Li, Weisen Shi, Wen Wu, Jaya Rao, Mushu Li, Hongli He and Conghao Zhou. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, IEEE Network and IEEE Open Journal of Vehicular Technology.

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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