Ping Fan
- Artificial Intelligence top 1%
- Computational Theory and Mathematics top 1%
- Computer Vision and Pattern Recognition top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Electrical and Electronic Engineering
- Co-authors
- Ri‐Gui ZhouWenWen HuHai-Sheng LiHaiying XiaShuxiang SongHuiling PengNaihuan JingYajuan Sun
- Topics
- Quantum Computing Algorithms and Architecture (34 papers)Quantum Information and Cryptography (28 papers)Quantum-Dot Cellular Automata (19 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Ping Fan
41 papers receiving 934 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 845
- Computational Theory and Mathematics 390
- Computer Vision and Pattern Recognition 223
- Atomic and Molecular Physics, and Optics 181
- Electrical and Electronic Engineering 64
Countries citing papers authored by Ping Fan
This map shows the geographic impact of Ping Fan'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 Ping Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ping Fan more than expected).
Fields of papers citing papers by Ping Fan
This network shows the impact of papers produced by Ping Fan. 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 Ping Fan. The network helps show where Ping Fan may publish in the future.
Co-authorship network of co-authors of Ping Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Ping Fan. A scholar is included among the top collaborators of Ping Fan 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 Ping Fan. Ping Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 9 | |
| 6 | 4 | |
| 7 | 24 | |
| 8 | 12 | |
| 9 | 70 | |
| 10 | 6 | |
| 11 | 37 | |
| 12 | 29 | |
| 13 | Quantum Gray-scale Image Dilation/Erosion Algorithm Based on Quantum Loading Scheme | 4 |
| 14 | 35 | |
| 15 | 40 | |
| 16 | 66 | |
| 17 | 4 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 20 |
About Ping Fan
Ping Fan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 43 papers that have together received 969 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (34 papers), Quantum Information and Cryptography (28 papers) and Quantum-Dot Cellular Automata (19 papers). The work is most often cited by research in Artificial Intelligence (845 citations), Computational Theory and Mathematics (390 citations) and Computer Vision and Pattern Recognition (223 citations). Ping Fan has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Ri‐Gui Zhou, WenWen Hu, Hai-Sheng Li, Haiying Xia, Shuxiang Song, Huiling Peng, Naihuan Jing, Yajuan Sun, Gui‐Lu Long and Hou Ian. Their work appears in journals such as Scientific Reports, Information Sciences and IEEE Transactions on Cybernetics.
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.