Jun Ai

541 citations
61 papers · 344 · h-index 10

Impact in

  • Software top 2%
    • Software Reliability and Analysis Research
    • Software Testing and Debugging Techniques
    • Software Engineering Research

Papers in

    • Software Reliability and Analysis Research 35
    • Software Testing and Debugging Techniques 14
    • Software Engineering Research 29

Jun Ai

53 papers receiving 331 citations

Peers

Jun Ai
Comparison fields: 5 of 56
  • Software 179
  • Information Systems 200
  • Computer Networks and Communications 120
  • Medical Laboratory Technology 7
  • Safety, Risk, Reliability and Quality 32
Replace Claudio Menghi with:
Claudio Menghi Italy
Leonardo Montecchi Italy
Mario Trapp Germany
Mario Gleirscher Germany
Yunwei Dong China
Paulo Romero Martins Maciel Brazil
Ken Keefe United States
Mehrdad Saadatmand Sweden
Erwin Schoitsch Austria
Stefano Sebastio Italy
Jun Ai relative to Claudio Menghi Italy Claudio Menghi's profile →
Citations per field
00.5×1.5×2.0×
Claudio Menghi · 1×
Citations per year

Countries citing papers authored by Jun Ai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202056
2 202225
3 202221
4 201920
5 201815
6 202215
7 202114
8 202013
9 201713
10 201710
11 20068
12 20178
13 20237
14 20127
15 20207
16 20207
17 20167
18 20156
19 20196
20 20205

About Jun Ai

Jun Ai is a scholar working on Software, Information Systems, Computer Networks and Communications, Artificial Intelligence and Safety, Risk, Reliability and Quality, having authored 61 papers that have together received 344 indexed citations. Recurring topics across this work include Software Reliability and Analysis Research (35 papers), Software Engineering Research (29 papers), Software System Performance and Reliability (20 papers), Software Testing and Debugging Techniques (14 papers), Anomaly Detection Techniques and Applications (8 papers), Reliability and Maintenance Optimization (5 papers), Complex Network Analysis Techniques (5 papers) and Adversarial Robustness in Machine Learning (4 papers). The work is most often cited by research in Software (179 citations), Information Systems (200 citations), Computer Networks and Communications (120 citations), Medical Laboratory Technology (7 citations) and Safety, Risk, Reliability and Quality (32 citations). Jun Ai has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Zhenning Xu, Jingyu Liu, Yihai He, Minyan Lu, Fei Wang, Yulei Sui, Ting Lin, Feng Zheng, Zhan Su and Yu Zhao. Their work appears in journals such as Applied Sciences, IEEE Transactions on Reliability, Physica A Statistical Mechanics and its Applications, Reliability Engineering & System Safety and IEEE Access.

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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