Ling‐Qi Yan
- Computer Graphics and Computer-Aided Design top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Computational Mechanics top 2%
- Atomic and Molecular Physics, and Optics
- Media Technology top 5%
- Co-authors
- Ravi RamamoorthiMiloš HašanSteve MarschnerWenzel JakobJason LawrenceKun XuHenrik Wann JensenJie Guo
- Topics
- Computer Graphics and Visualization Techniques (67 papers)Advanced Vision and Imaging (48 papers)3D Shape Modeling and Analysis (34 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- ACM Transactions on GraphicsIEEE Transactions on Visualization and Computer GraphicsComputer Graphics Forum
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Ling‐Qi Yan
69 papers receiving 874 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Computer Graphics and Computer-Aided Design 695
- Computer Vision and Pattern Recognition 650
- Computational Mechanics 463
- Atomic and Molecular Physics, and Optics 72
- Media Technology 56
Countries citing papers authored by Ling‐Qi Yan
This map shows the geographic impact of Ling‐Qi Yan'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 Ling‐Qi Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling‐Qi Yan more than expected).
Fields of papers citing papers by Ling‐Qi Yan
This network shows the impact of papers produced by Ling‐Qi Yan. 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 Ling‐Qi Yan. The network helps show where Ling‐Qi Yan may publish in the future.
Co-authorship network of co-authors of Ling‐Qi Yan
This figure shows the co-authorship network connecting the top 25 collaborators of Ling‐Qi Yan. A scholar is included among the top collaborators of Ling‐Qi Yan 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 Ling‐Qi Yan. Ling‐Qi Yan 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 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | 6 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 6 | |
| 15 | 14 | |
| 16 | 8 | |
| 17 | 2 | |
| 18 | 0 | |
| 19 | 15 | |
| 20 | Physically-based Modeling and Rendering of Complex Visual Appearance | 1 |
About Ling‐Qi Yan
Ling‐Qi Yan is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Acoustics and Ultrasonics, having authored 80 papers that have together received 911 indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (67 papers), Advanced Vision and Imaging (48 papers) and 3D Shape Modeling and Analysis (34 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (695 citations), Computer Vision and Pattern Recognition (650 citations) and Computational Mechanics (463 citations). Ling‐Qi Yan has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Ravi Ramamoorthi, Miloš Hašan, Steve Marschner, Wenzel Jakob, Jason Lawrence, Kun Xu, Henrik Wann Jensen, Jie Guo, Yanwen Guo and Beibei Wang. Their work appears in journals such as ACM Transactions on Graphics, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.
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.