Debin Liu
- Artificial Intelligence top 10%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Topics
- Tensor decomposition and applications (6 papers)Privacy-Preserving Technologies in Data (5 papers)Internet Traffic Analysis and Secure E-voting (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Communications Surveys & Tutorials
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Debin Liu
29 papers receiving 343 citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 127
- Information Systems 122
- Computer Networks and Communications 74
- Computer Vision and Pattern Recognition 44
- Electrical and Electronic Engineering 42
Countries citing papers authored by Debin Liu
This map shows the geographic impact of Debin Liu'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 Debin Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debin Liu more than expected).
Fields of papers citing papers by Debin Liu
This network shows the impact of papers produced by Debin Liu. 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 Debin Liu. The network helps show where Debin Liu may publish in the future.
Co-authorship network of co-authors of Debin Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Debin Liu. A scholar is included among the top collaborators of Debin Liu 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 Debin Liu. Debin Liu 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 | 4 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 2 | |
| 11 | 20 | |
| 12 | 1 | |
| 13 | 8 | |
| 14 | 9 | |
| 15 | 12 | |
| 16 | 23 | |
| 17 | 1 | |
| 18 | 25 | |
| 19 | Mental Models of Computer Security Risks. | 34 |
| 20 | Proof of Work can Work. | 21 |
About Debin Liu
Debin Liu is a scholar working on Computational Mathematics, Artificial Intelligence and Computer Science Applications, having authored 34 papers that have together received 357 indexed citations. Recurring topics across this work include Tensor decomposition and applications (6 papers), Privacy-Preserving Technologies in Data (5 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). The work is most often cited by research in Computational Mathematics (8 citations), Health Informatics (10 citations) and Information Systems (122 citations). Debin Liu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include L. Jean Camp, Laurence T. Yang, Jean Camp, Xiaofeng Wang, Mi Lu, Xianjun Deng, Shan Jin, Zhi Zhou, Yijun Mo and Qingxiao Chen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Communications Surveys & Tutorials.
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.