Guanjun Lin
Impact in
- Software top 1%
- Software Reliability and Analysis Research
- Software Testing and Debugging Techniques
- Signal Processing top 1%
- Advanced Malware Detection Techniques
Papers in
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- Software Engineering Research 15
- Web Application Security Vulnerabilities 4
- Spam and Phishing Detection 2
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- Advanced Malware Detection Techniques 16
- Co-authors
- Yang Xiang (7 shared papers)Jun Zhang (9 shared papers)Sheng Wen (2 shared papers)Qing‐Long Han (2 shared papers)Lei Pan (4 shared papers)Wei Luo (3 shared papers)Olivier De Vel (3 shared papers)Paul Montague (3 shared papers)
In The Last Decade
Guanjun Lin
24 papers receiving 1.0k citations
Guanjun Lin's Hit Papers
Peers
Comparison fields: 5 of 76
- Software 421
- Signal Processing 581
- Information Systems 753
- Health Informatics 22
- Computer Networks and Communications 328
Countries citing papers authored by Guanjun Lin
This map shows the geographic impact of Guanjun Lin'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 Guanjun Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guanjun Lin more than expected).
Fields of papers citing papers by Guanjun Lin
This network shows the impact of papers produced by Guanjun Lin. 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 Guanjun Lin. The network helps show where Guanjun Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Guanjun Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Software Vulnerability Detection Using Deep Neural Networks: A Survey Hit paper breakdown → | 2020 | 295 |
| 2 | 2018 | 148 | |
| 3 | 2017 | 92 | |
| 4 | 2019 | 86 | |
| 5 | 2019 | 84 | |
| 6 | 2020 | 80 | |
| 7 | 2020 | 53 | |
| 8 | 2020 | 49 | |
| 9 | 2020 | 46 | |
| 10 | 2017 | 35 | |
| 11 | 2022 | 24 | |
| 12 | 2021 | 20 | |
| 13 | 2021 | 9 | |
| 14 | 2022 | 8 | |
| 15 | 2023 | 7 | |
| 16 | 2020 | 6 | |
| 17 | 2024 | 6 | |
| 18 | 2022 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2022 | 4 |
About Guanjun Lin
Guanjun Lin is a scholar working on Information Systems, Signal Processing, Software, Computer Networks and Communications and Artificial Intelligence, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (16 papers), Software Engineering Research (15 papers), Software Reliability and Analysis Research (9 papers), Network Security and Intrusion Detection (4 papers), Web Application Security Vulnerabilities (4 papers), COVID-19 diagnosis using AI (2 papers), Spam and Phishing Detection (2 papers) and Metaheuristic Optimization Algorithms Research (2 papers). The work is most often cited by research in Software (421 citations), Signal Processing (581 citations), Information Systems (753 citations), Health Informatics (22 citations) and Computer Networks and Communications (328 citations). Guanjun Lin has collaborated with scholars based in China, Australia and Egypt. Frequent co-authors include Yang Xiang, Jun Zhang, Sheng Wen, Qing‐Long Han, Lei Pan, Wei Luo, Olivier De Vel, Paul Montague, Yonghang Tai and Jun Zhang. Their work appears in journals such as IEEE Access, Journal of Information Security and Applications, Neural Computing and Applications, IEEE Transactions on Dependable and Secure Computing and Journal of Computational Design 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.