L. Han
Impact in
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- Network Security and Intrusion Detection
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- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle physics theoretical and experimental studies
Papers in
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- Network Security and Intrusion Detection 3
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- Quantum Chromodynamics and Particle Interactions 3
- High-Energy Particle Collisions Research 3
- Particle physics theoretical and experimental studies 3
- Co-authors
- Chun Hu (2 shared papers)Wei Wang (1 shared paper)Jun Chen (1 shared paper)Li Yang (1 shared paper)Min Yang (1 shared paper)Haibo Wang (1 shared paper)Xuexiang Hu (1 shared paper)Y. G. (3 shared papers)
In The Last Decade
L. Han
11 papers receiving 228 citations
Peers
Comparison fields: 5 of 57
- Computer Networks and Communications 85
- Nuclear and High Energy Physics 45
- Signal Processing 35
- Artificial Intelligence 73
- Health, Toxicology and Mutagenesis 27
Countries citing papers authored by L. Han
This map shows the geographic impact of L. Han'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 L. Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. Han more than expected).
Fields of papers citing papers by L. Han
This network shows the impact of papers produced by L. Han. 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 L. Han. The network helps show where L. Han may publish in the future.
Co-authors
The 25 scholars most cited alongside L. Han, 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 | 2018 | 52 | |
| 2 | 2016 | 48 | |
| 3 | 2011 | 37 | |
| 4 | 2015 | 32 | |
| 5 | 2024 | 29 | |
| 6 | 2019 | 17 | |
| 7 | 2014 | 6 | |
| 8 | 2024 | 4 | |
| 9 | 2021 | 3 | |
| 10 | 2011 | 2 | |
| 11 | 2025 | 1 |
About L. Han
L. Han is a scholar working on Computer Networks and Communications, Nuclear and High Energy Physics, Information Systems, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 11 papers that have together received 231 indexed citations. Recurring topics across this work include Quantum Chromodynamics and Particle Interactions (3 papers), Network Security and Intrusion Detection (3 papers), High-Energy Particle Collisions Research (3 papers), Particle physics theoretical and experimental studies (3 papers), Environmental remediation with nanomaterials (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Video Surveillance and Tracking Methods (1 paper) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Computer Networks and Communications (85 citations), Nuclear and High Energy Physics (45 citations), Signal Processing (35 citations), Artificial Intelligence (73 citations) and Health, Toxicology and Mutagenesis (27 citations). L. Han has collaborated with scholars based in China, Singapore and Taiwan. Frequent co-authors include Chun Hu, Wei Wang, Jun Chen, Li Yang, Min Yang, Haibo Wang, Xuexiang Hu, Y. G., Zhan Chen and Haibo Wang. Their work appears in journals such as International Journal of Emerging Technologies in Learning (iJET), IEEE Transactions on Instrumentation and Measurement, The Professional Geographer, IEEE/CAA Journal of Automatica Sinica 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.