Ming Yan

2.5k citations
86 papers · 1.3k · h-index 19

Impact in

Papers in

Ming Yan

79 papers receiving 1.2k citations

Peers

Ming Yan
Comparison fields: 5 of 98
  • Computational Mechanics 571
  • Numerical Analysis 106
  • Computer Vision and Pattern Recognition 301
  • Computer Networks and Communications 232
  • Computational Mathematics 6
Replace Jinming Wen with:
Jinming Wen China
Brendan O’Donoghue United States
Rachel Ward United States
Rodolphe Jenatton France
Afonso S. Bandeira United States
C. Si̇nan Güntürk United States
Simon Setzer Germany
Xiaojing Ye United States
Penghang Yin United States
Ming Yan relative to Jinming Wen China Jinming Wen's profile →
Citations per field
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Jinming Wen · 1×
Citations per year

Countries citing papers authored by Ming Yan

Since Specialization
Citations

This map shows the geographic impact of Ming 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 Ming Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Yan more than expected).

Fields of papers citing papers by Ming Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming 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 Ming Yan. The network helps show where Ming Yan may publish in the future.

Co-authors

The 25 scholars most cited alongside Ming Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ming Yan Line = papers co-authored together Ming Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019124
2 2017124
3 2012120
4 201879
5 201964
6 201959
7 200748
8 201347
9 202043
10 201641
11 201629
12 202128
13 201624
14 202021
15 201121
16 198820
17 202020
18 201720
19 201618
20 201218

About Ming Yan

Ming Yan is a scholar working on Computational Mechanics, Biomedical Engineering, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 86 papers that have together received 1.3k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (29 papers), Medical Imaging Techniques and Applications (14 papers), Advanced X-ray and CT Imaging (12 papers), Distributed Control Multi-Agent Systems (10 papers), Image and Signal Denoising Methods (10 papers), Microwave Imaging and Scattering Analysis (8 papers), Radiation Dose and Imaging (7 papers) and Advanced Fiber Optic Sensors (7 papers). The work is most often cited by research in Computational Mechanics (571 citations), Numerical Analysis (106 citations), Computer Vision and Pattern Recognition (301 citations), Computer Networks and Communications (232 citations) and Computational Mathematics (6 citations). Ming Yan has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Yifei Lou, Stanley Osher, Yi Yang, Wei Shi, Zhi Li, Wotao Yin, Tieyong Zeng, Zhimin Peng, Jun Liu and Luminita A. Vese. Their work appears in journals such as Journal of Scientific Computing, IEEE Transactions on Signal Processing, Journal of Computational Physics, Inverse Problems and Imaging and Computerized Medical Imaging and 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.

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