Long Ma

1.1k citations
86 papers · 854 · h-index 12

Impact in

Papers in

Long Ma

75 papers receiving 822 citations

Peers

Long Ma
Comparison fields: 5 of 81
  • Polymers and Plastics 296
  • Biomedical Engineering 530
  • Cognitive Neuroscience 133
  • Electronic, Optical and Magnetic Materials 111
  • Computer Vision and Pattern Recognition 110
Replace Minsong Wei with:
Minsong Wei China
Chao Tang China
Charles R. Tolle United States
Yu Xiaoguang China
Zhenkun Li China
Chenglong Hao China
Jae‐Ho Lee South Korea
Guoliang Ma China
Jianxiang Wang China
Sang-Il Lee South Korea
Long Ma relative to Minsong Wei China Minsong Wei's profile →
Citations per field
00.5×3.9×
Minsong Wei · 1×
Citations per year

Countries citing papers authored by Long Ma

Since Specialization
Citations

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

Fields of papers citing papers by Long Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Long Ma, 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 Long Ma Line = papers co-authored together Long Ma 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 2016222
2 2018149
3 201692
4 202220
5 202219
6 202018
7 201916
8 202014
9 202213
10 201612
11 202111
12 201811
13 200910
14 202310
15 201210
16 201110
17 201110
18 20219
19 20179
20 20219

About Long Ma

Long Ma is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Mechanical Engineering, Biomedical Engineering and Computational Mechanics, having authored 86 papers that have together received 854 indexed citations. Recurring topics across this work include Optical measurement and interference techniques (21 papers), Advanced Measurement and Metrology Techniques (15 papers), Advanced Fiber Optic Sensors (11 papers), Photonic and Optical Devices (9 papers), Advancements in Photolithography Techniques (8 papers), Surface Roughness and Optical Measurements (8 papers), Electron and X-Ray Spectroscopy Techniques (5 papers) and Arctic and Russian Policy Studies (5 papers). The work is most often cited by research in Polymers and Plastics (296 citations), Biomedical Engineering (530 citations), Cognitive Neuroscience (133 citations), Electronic, Optical and Magnetic Materials (111 citations) and Computer Vision and Pattern Recognition (110 citations). Long Ma has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Shuwen Chen, Zhong Lin Wang, Xia Cao, M. Willander, Ning Wang, Hui Zhu, Nan Wu, Jun Zhou, Shizhe Lin and Bo Wang. Their work appears in journals such as Optics and Lasers in Engineering, Measurement, Optics Communications, Applied Optics and Advanced Energy Materials.

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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