Limin Yang
Impact in
- Signal Processing top 5%
- Advanced Malware Detection Techniques
- Software top 10%
- Software Testing and Debugging Techniques
Papers in
-
- Advanced Malware Detection Techniques 10
- Direction-of-Arrival Estimation Techniques 1
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- Spam and Phishing Detection 4
- Information and Cyber Security 2
- Co-authors
- Gang Wang (7 shared papers)Linhai Song (3 shared papers)Arridhana Ciptadi (3 shared papers)Peng Peng (1 shared paper)Gang Wang (1 shared paper)Xinyu Xing (2 shared papers)Hang Hu (2 shared papers)Ziyi Zhang (2 shared papers)
- Journals
- Peer-to-Peer Networking and Applications (1 paper)UCL Discovery (University College London) (1 paper)USENIX Security Symposium (2 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Limin Yang
13 papers receiving 324 citations
Peers
Comparison fields: 5 of 41
- Signal Processing 225
- Software 44
- Computer Networks and Communications 183
- Information Systems 166
- Artificial Intelligence 135
Countries citing papers authored by Limin Yang
This map shows the geographic impact of Limin Yang'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 Limin Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Limin Yang more than expected).
Fields of papers citing papers by Limin Yang
This network shows the impact of papers produced by Limin Yang. 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 Limin Yang. The network helps show where Limin Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Limin Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 80 | |
| 2 | 2019 | 71 | |
| 3 | CADE: Detecting and explaining concept drift samples for security applications | 2021 | 42 |
| 4 | Understanding the reproducibility of crowd-reported security vulnerabilities | 2018 | 38 |
| 5 | Measuring and Modeling the Label Dynamics of Online Anti-Malware Engines | 2020 | 32 |
| 6 | 2017 | 14 | |
| 7 | 2020 | 13 | |
| 8 | 2020 | 13 | |
| 9 | 2023 | 11 | |
| 10 | 2016 | 11 | |
| 11 | 2011 | 3 | |
| 12 | 2020 | 2 | |
| 13 | 2023 | 2 |
About Limin Yang
Limin Yang is a scholar working on Signal Processing, Information Systems, Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering, having authored 13 papers that have together received 332 indexed citations. Recurring topics across this work include Advanced Malware Detection Techniques (10 papers), Network Security and Intrusion Detection (6 papers), Spam and Phishing Detection (4 papers), Data Stream Mining Techniques (3 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Information and Cyber Security (2 papers), Adversarial Robustness in Machine Learning (1 paper) and Direction-of-Arrival Estimation Techniques (1 paper). The work is most often cited by research in Signal Processing (225 citations), Software (44 citations), Computer Networks and Communications (183 citations), Information Systems (166 citations) and Artificial Intelligence (135 citations). Limin Yang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Gang Wang, Linhai Song, Arridhana Ciptadi, Peng Peng, Gang Wang, Xinyu Xing, Hang Hu, Ziyi Zhang, Wenbo Guo and Dongliang Mu. Their work appears in journals such as Peer-to-Peer Networking and Applications, UCL Discovery (University College London) and USENIX Security Symposium.
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.