Luyao Ren

408 citations
23 papers · 300 · h-index 10

Impact in

Papers in

    • Software Engineering Research 7
    • Software Testing and Debugging Techniques 6
    • Software Reliability and Analysis Research 3

Luyao Ren

21 papers receiving 294 citations

Peers

Luyao Ren
Comparison fields: 5 of 66
  • Software 79
  • Computer Science Applications 26
  • Information Systems 101
  • Water Science and Technology 47
  • Signal Processing 30
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Jonathan Dorn United States
T. R. Gopalakrishnan Nair India
Nasser Alzeidi Oman
P. Anbalagan United States
Hanady M. Abdulsalam Kuwait
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Citations per field
00.5×9.4×
Jonathan Dorn · 1×
Citations per year

Countries citing papers authored by Luyao Ren

Since Specialization
Citations

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

Fields of papers citing papers by Luyao Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201950
2 202048
3 201927
4 202025
5 202224
6 201523
7 202316
8 202015
9 202412
10 201910
11 20239
12 20207
13 20186
14 20226
15 20245
16 20235
17 20233
18
Poster: Forks Insight: Providing an Overview of GitHub Forks
20183
19 20233
20 20242

About Luyao Ren

Luyao Ren is a scholar working on Information Systems, Software, Biomedical Engineering, Artificial Intelligence and Electrical and Electronic Engineering, having authored 23 papers that have together received 300 indexed citations. Recurring topics across this work include Software Engineering Research (7 papers), Software Testing and Debugging Techniques (6 papers), Membrane-based Ion Separation Techniques (6 papers), Fuel Cells and Related Materials (4 papers), Software Reliability and Analysis Research (3 papers), Advanced Software Engineering Methodologies (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Membrane Separation Technologies (2 papers). The work is most often cited by research in Software (79 citations), Computer Science Applications (26 citations), Information Systems (101 citations), Water Science and Technology (47 citations) and Signal Processing (30 citations). Luyao Ren has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yingfei Xiong, Qingbai Chen, Jinli Zhao, Jiajun Jiang, Lingming Zhang, Tao Xie, Jianyou Wang, Shurui Zhou, Christian Kästner and Yuhao Zhang. Their work appears in journals such as Journal of Membrane Science, ACM Transactions on Software Engineering and Methodology, European Journal of Medicinal Chemistry, BioMed Research International and Desalination.

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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