Hui Lu

1.4k citations
55 papers · 826 · h-index 16

Impact in

Papers in

Hui Lu

51 papers receiving 800 citations

Peers

Hui Lu
Comparison fields: 5 of 92
  • Signal Processing 204
  • Computer Networks and Communications 354
  • Artificial Intelligence 351
  • Information Systems 188
  • Software 28
Replace Haifeng Chen with:
Haifeng Chen United States
Zahra Pooranian Italy
Suprio Ray Canada
Mohammad Alsmirat Jordan
Alex Delis Greece
Hiroshi Esaki Japan
Philipp Richter United States
Jieren Cheng China
Noura Limam Canada
Hui Lu relative to Haifeng Chen United States Haifeng Chen's profile →
Citations per field
00.5×3.5×
Haifeng Chen · 1×
Citations per year

Countries citing papers authored by Hui Lu

Since Specialization
Citations

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

Fields of papers citing papers by Hui Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019114
2 202076
3 202164
4 202061
5 201955
6 202147
7 202043
8 202029
9 202027
10 201927
11 202024
12 202124
13 202222
14 202021
15 202020
16 202319
17 202014
18 202312
19 202410
20 202110

About Hui Lu

Hui Lu is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Information Systems and Electrical and Electronic Engineering, having authored 55 papers that have together received 826 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (19 papers), Network Security and Intrusion Detection (14 papers), IoT and Edge/Fog Computing (6 papers), Internet Traffic Analysis and Secure E-voting (6 papers), Security and Verification in Computing (6 papers), Anomaly Detection Techniques and Applications (5 papers), Software Testing and Debugging Techniques (5 papers) and Blockchain Technology Applications and Security (4 papers). The work is most often cited by research in Signal Processing (204 citations), Computer Networks and Communications (354 citations), Artificial Intelligence (351 citations), Information Systems (188 citations) and Software (28 citations). Hui Lu has collaborated with scholars based in China, United States and Qatar. Frequent co-authors include Zhihong Tian, Yanbin Sun, Xiaojiang Du, Sabita Maharjan, Mohan Li, Mohsen Guizani, Lihua Yin, Chunsheng Zhu, Ning Hu and Shen Su. Their work appears in journals such as IEEE Network, IEEE Internet of Things Journal, IEEE Access, IEEE Transactions on Cloud Computing and IEEE Transactions on Network Science and Engineering.

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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