Miao Jin
- Computational Mechanics top 2%
- Computer Graphics and Computer-Aided Design top 0.5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Topics
- 3D Shape Modeling and Analysis (18 papers)Advanced Numerical Analysis Techniques (15 papers)Computer Graphics and Visualization Techniques (14 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputational MechanicsComputer Vision and Pattern Recognition
- Journals
- IEEE Internet of Things JournalIEEE/ACM Transactions on NetworkingIEEE Transactions on Visualization and Computer Graphics
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Miao Jin
51 papers receiving 932 citations
Peers
Comparison fields: 5 of 78
- Computational Mechanics 524
- Computer Graphics and Computer-Aided Design 461
- Computer Networks and Communications 237
- Computer Vision and Pattern Recognition 227
- Electrical and Electronic Engineering 158
Countries citing papers authored by Miao Jin
This map shows the geographic impact of Miao Jin'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 Miao Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miao Jin more than expected).
Fields of papers citing papers by Miao Jin
This network shows the impact of papers produced by Miao Jin. 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 Miao Jin. The network helps show where Miao Jin may publish in the future.
Co-authorship network of co-authors of Miao Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Miao Jin. A scholar is included among the top collaborators of Miao Jin 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 Miao Jin. Miao Jin 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 | 2 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 10 | |
| 7 | 5 | |
| 8 | 29 | |
| 9 | 23 | |
| 10 | 23 | |
| 11 | 57 | |
| 12 | 7 | |
| 13 | 25 | |
| 14 | 1 | |
| 15 | 188 | |
| 16 | 44 | |
| 17 | 10 | |
| 18 | 39 | |
| 19 | 1 | |
| 20 | 2 |
About Miao Jin
Miao Jin is a scholar working on Computer Graphics and Computer-Aided Design, Computational Mechanics and Ocean Engineering, having authored 52 papers that have together received 968 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (18 papers), Advanced Numerical Analysis Techniques (15 papers) and Computer Graphics and Visualization Techniques (14 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (461 citations), Computational Mechanics (524 citations) and Computer Vision and Pattern Recognition (227 citations). Miao Jin has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Xianfeng Gu, Feng Luo, Hongyi Wu, Joondong Kim, Xiaohu Guo, Ying He, Shing Tung Yau, Yalin Wang, Hong Qin and Guodong Rong. Their work appears in journals such as IEEE Internet of Things Journal, IEEE/ACM Transactions on Networking and IEEE Transactions on Visualization and Computer Graphics.
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.