Chen Wu

27 papers receiving 444 citations

Peers

Chen Wu
Comparison fields: 5 of 61
  • Biomedical Engineering 215
  • Ceramics and Composites 23
  • Computational Mechanics 81
  • Electronic, Optical and Magnetic Materials 71
  • Surfaces, Coatings and Films 23
Replace William D. Brown with:
William D. Brown United States
Weibing Wang China
O. Ehrmann Germany
Y.K. Fang Taiwan
Sourabh Roy India
Bin Du China
E. Hourdakis Greece
Xiangdong Liang United States
Hayato Iwamoto Japan
Wen-Wei Shen Taiwan
Chen Wu relative to William D. Brown United States William D. Brown's profile →
Citations per field
00.5×9.3×
William D. Brown · 1×
Citations per year

Countries citing papers authored by Chen Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chen Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chen Wu, 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 Chen Wu Line = papers co-authored together Chen Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202347
2 202045
3 202143
4 201942
5 201830
6 201628
7 202228
8 202125
9 201319
10 202219
11 201719
12 202017
13 202415
14 202015
15 202314
16 202313
17 20196
18 20146
19 20144
20
Exploring Forensic Dental Identification with Deep Learning
20213

About Chen Wu

Chen Wu is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering, Materials Chemistry, Computer Vision and Pattern Recognition and Mechanics of Materials, having authored 28 papers that have together received 450 indexed citations. Recurring topics across this work include Diamond and Carbon-based Materials Research (7 papers), Advanced Surface Polishing Techniques (5 papers), Face and Expression Recognition (4 papers), Nanowire Synthesis and Applications (4 papers), Emotion and Mood Recognition (4 papers), Metal and Thin Film Mechanics (3 papers), Laser Material Processing Techniques (3 papers) and Plasma Diagnostics and Applications (3 papers). The work is most often cited by research in Biomedical Engineering (215 citations), Ceramics and Composites (23 citations), Computational Mechanics (81 citations), Electronic, Optical and Magnetic Materials (71 citations) and Surfaces, Coatings and Films (23 citations). Chen Wu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Xudong Fang, Zhuangde Jiang, Ryutaro Maeda, Libo Zhao, Bian Tian, Qiang Kang, Lijun Wang, Shenli Jia, Jing Zhao and Guojun Weng. Their work appears in journals such as Ceramics International, Microsystems & Nanoengineering, Applied Surface Science, Multimedia Tools and Applications and Review of Scientific Instruments.

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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