Kai Lu

837 citations
57 papers · 552 · h-index 11

Impact in

Papers in

Kai Lu

48 papers receiving 533 citations

Peers

Kai Lu
Comparison fields: 5 of 66
  • Hardware and Architecture 266
  • Software 59
  • Computer Networks and Communications 331
  • Information Systems 129
  • Signal Processing 57
Replace Lifan Xu with:
Lifan Xu United States
Yonghong Yan United States
Leonardo Bautista-Gomez Spain
José Pedro Magalhães Netherlands
Xinmin Tian United States
Chris Gregg United States
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Dror E. Maydan United States
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Kai Lu relative to Lifan Xu United States Lifan Xu's profile →
Citations per field
00.5×1.5×2×2.3×
Lifan Xu · 1×
Citations per year

Countries citing papers authored by Kai Lu

Since Specialization
Citations

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

Fields of papers citing papers by Kai Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011120
2 201062
3 201842
4 202240
5 201439
6 202026
7 201222
8 201418
9 201814
10 201512
11 202312
12 201311
13 201511
14 20159
15 20148
16 20138
17 20198
18 20227
19 20126
20 20166

About Kai Lu

Kai Lu is a scholar working on Hardware and Architecture, Computer Networks and Communications, Software, Information Systems and Artificial Intelligence, having authored 57 papers that have together received 552 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (38 papers), Advanced Data Storage Technologies (14 papers), Distributed and Parallel Computing Systems (13 papers), Distributed systems and fault tolerance (13 papers), Software Testing and Debugging Techniques (10 papers), Interconnection Networks and Systems (7 papers), Radiation Effects in Electronics (5 papers) and Security and Verification in Computing (4 papers). The work is most often cited by research in Hardware and Architecture (266 citations), Software (59 citations), Computer Networks and Communications (331 citations), Information Systems (129 citations) and Signal Processing (57 citations). Kai Lu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Xu Zhou, Xiaoping Wang, Xiangke Liao, Xuejun Yang, Qingfeng Hu, Jinshu Su, Junqiang Song, Tom Bergan, Canqun Yang and Jianbin Fang. Their work appears in journals such as ACM SIGPLAN Notices, Journal of Neuroscience, IEEE Transactions on Computers, Systems Science & Control Engineering and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

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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