Wei‐Min Shi
- Artificial Intelligence top 1%
- Atomic and Molecular Physics, and Optics top 5%
- Computer Vision and Pattern Recognition top 2%
- Computational Theory and Mathematics top 2%
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Yi‐Hua ZhouYu‐Guang YangXiu‐Bo ChenDan LiJu TianZhichao LiuXin LiaoJian Li
- Topics
- Quantum Information and Cryptography (68 papers)Quantum Computing Algorithms and Architecture (64 papers)Quantum Mechanics and Applications (48 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionAtomic and Molecular Physics, and Optics
- Partner nations
- ChinaBulgariaUzbekistan
In The Last Decade
Wei‐Min Shi
101 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 1.0k
- Atomic and Molecular Physics, and Optics 701
- Computer Vision and Pattern Recognition 514
- Computational Theory and Mathematics 201
- Statistical and Nonlinear Physics 63
Countries citing papers authored by Wei‐Min Shi
This map shows the geographic impact of Wei‐Min Shi'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 Wei‐Min Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei‐Min Shi more than expected).
Fields of papers citing papers by Wei‐Min Shi
This network shows the impact of papers produced by Wei‐Min Shi. 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 Wei‐Min Shi. The network helps show where Wei‐Min Shi may publish in the future.
Co-authorship network of co-authors of Wei‐Min Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Wei‐Min Shi. A scholar is included among the top collaborators of Wei‐Min Shi 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 Wei‐Min Shi. Wei‐Min Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 10 | |
| 9 | 6 | |
| 10 | 4 | |
| 11 | 17 | |
| 12 | 10 | |
| 13 | 6 | |
| 14 | 35 | |
| 15 | 19 | |
| 16 | 75 | |
| 17 | 13 | |
| 18 | Enhanced Identity-based Deniable Authentication Protocol | 1 |
| 19 | 0 | |
| 20 | 4 |
About Wei‐Min Shi
Wei‐Min Shi is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computer Vision and Pattern Recognition, having authored 109 papers that have together received 1.5k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (68 papers), Quantum Computing Algorithms and Architecture (64 papers) and Quantum Mechanics and Applications (48 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computer Vision and Pattern Recognition (514 citations) and Atomic and Molecular Physics, and Optics (701 citations). Wei‐Min Shi has collaborated with scholars based in China, Bulgaria and Uzbekistan. Frequent co-authors include Yi‐Hua Zhou, Yu‐Guang Yang, Xiu‐Bo Chen, Dan Li, Ju Tian, Zhichao Liu, Xin Liao, Jian Li, Weifeng Cao and Peng Xu. Their work appears in journals such as Journal of Agricultural and Food Chemistry, Scientific Reports and Sensors.
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.