Liang Tan
- Information Systems top 0.5%
- Artificial Intelligence top 1%
- Computer Networks and Communications top 1%
- Electrical and Electronic Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Keping YuNa ShiXiaofan ChengYaser JararwehMoayad AloqailyLong LinCaixia YangGautam Srivastava
- Topics
- Blockchain Technology Applications and Security (21 papers)Privacy-Preserving Technologies in Data (12 papers)IoT and Edge/Fog Computing (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessIEEE Communications Magazine
- Partner nations
- ChinaJapanUnited Kingdom
In The Last Decade
Liang Tan
42 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Information Systems 969
- Artificial Intelligence 896
- Computer Networks and Communications 870
- Electrical and Electronic Engineering 695
- Computer Vision and Pattern Recognition 320
Countries citing papers authored by Liang Tan
This map shows the geographic impact of Liang Tan'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 Liang Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liang Tan more than expected).
Fields of papers citing papers by Liang Tan
This network shows the impact of papers produced by Liang Tan. 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 Liang Tan. The network helps show where Liang Tan may publish in the future.
Co-authorship network of co-authors of Liang Tan
This figure shows the co-authorship network connecting the top 25 collaborators of Liang Tan. A scholar is included among the top collaborators of Liang Tan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liang Tan. Liang Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 116 | |
| 7 | 88 | |
| 8 | Deep-Learning-Empowered Breast Cancer Auxiliary Diagnosis for 5GB Remote E-Healthbreakdown → | 200 |
| 9 | 90 | |
| 10 | 14 | |
| 11 | 118 | |
| 12 | 221 | |
| 13 | 121 | |
| 14 | Research and Progress in Computational Thinking | 1 |
| 15 | 1 | |
| 16 | Fake-honeypot Detection Method for Semi-distributed Peer-to-Peer Botnet | 3 |
| 17 | Detection methods research of half distributed P2P Botnet | 1 |
| 18 | 1 | |
| 19 | Comparing of CC and SSE-CMM | 2 |
| 20 | Search of Security Evaluation Criteria | 0 |
About Liang Tan
Liang Tan is a scholar working on Information Systems, Computer Networks and Communications and Artificial Intelligence, having authored 49 papers that have together received 2.3k indexed citations. Recurring topics across this work include Blockchain Technology Applications and Security (21 papers), Privacy-Preserving Technologies in Data (12 papers) and IoT and Edge/Fog Computing (9 papers). The work is most often cited by research in Information Systems (969 citations), Computer Networks and Communications (870 citations) and Artificial Intelligence (896 citations). Liang Tan has collaborated with scholars based in China, Japan and United Kingdom. Frequent co-authors include Keping Yu, Na Shi, Xiaofan Cheng, Yaser Jararweh, Moayad Aloqaily, Long Lin, Caixia Yang, Gautam Srivastava, Ali Kashif Bashir and Takuro Sato. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Communications Magazine.
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.