Yuan-Chen Guo
- Condensed Matter Physics top 5%
- Computer Vision and Pattern Recognition top 5%
- Electronic, Optical and Magnetic Materials
- Biomedical Engineering
- Computer Graphics and Computer-Aided Design top 2%
- Co-authors
- Huan LiuShi Xue DouSong–Hai ZhangYu HeDi KangLinchao BaoChen WangJueshi Qian
- Topics
- Physics of Superconductivity and Magnetism (22 papers)Superconducting Materials and Applications (14 papers)Computer Graphics and Visualization Techniques (12 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignCondensed Matter PhysicsComputer Vision and Pattern Recognition
- Journals
- Applied Physics LettersIEEE Transactions on Pattern Analysis and Machine IntelligenceScientific Reports
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Yuan-Chen Guo
55 papers receiving 773 citations
Peers
Comparison fields: 5 of 81
- Condensed Matter Physics 284
- Computer Vision and Pattern Recognition 283
- Electronic, Optical and Magnetic Materials 157
- Biomedical Engineering 152
- Computer Graphics and Computer-Aided Design 138
Countries citing papers authored by Yuan-Chen Guo
This map shows the geographic impact of Yuan-Chen Guo'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 Yuan-Chen Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuan-Chen Guo more than expected).
Fields of papers citing papers by Yuan-Chen Guo
This network shows the impact of papers produced by Yuan-Chen Guo. 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 Yuan-Chen Guo. The network helps show where Yuan-Chen Guo may publish in the future.
Co-authorship network of co-authors of Yuan-Chen Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Yuan-Chen Guo. A scholar is included among the top collaborators of Yuan-Chen Guo 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 Yuan-Chen Guo. Yuan-Chen Guo 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 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 9 | |
| 11 | 15 | |
| 12 | 1 | |
| 13 | 51 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 17 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | 19 | |
| 20 | 33 |
About Yuan-Chen Guo
Yuan-Chen Guo is a scholar working on Computer Graphics and Computer-Aided Design, Condensed Matter Physics and Electronic, Optical and Magnetic Materials, having authored 60 papers that have together received 808 indexed citations. Recurring topics across this work include Physics of Superconductivity and Magnetism (22 papers), Superconducting Materials and Applications (14 papers) and Computer Graphics and Visualization Techniques (12 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (138 citations), Condensed Matter Physics (284 citations) and Computer Vision and Pattern Recognition (283 citations). Yuan-Chen Guo has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Huan Liu, Shi Xue Dou, Song–Hai Zhang, Yu He, Di Kang, Linchao Bao, Chen Wang, Jueshi Qian, Yu‐Kun Lai and Tian-Xing Xu. Their work appears in journals such as Applied Physics Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.