Zhao Jun

1.2k citations
87 papers · 875 · h-index 19

Impact in

Papers in

Zhao Jun

77 papers receiving 844 citations

Peers

Zhao Jun
Comparison fields: 5 of 89
  • Ecological Modeling 134
  • Mechanical Engineering 485
  • Biomedical Engineering 562
  • Computational Mechanics 158
  • Computer Vision and Pattern Recognition 94
Replace Ji Zhao with:
Ji Zhao China
Haobo Cheng China
Meiping Wu China
Zhichao Dong China
Mustafa Ay Türkiye
H. Wang China
Xiaochao Li China
Duo Li China
Paul Shore United Kingdom
Zhenyuan Jia China
Zhao Jun relative to Ji Zhao China Ji Zhao's profile →
Citations per field
00.5×4.2×
Ji Zhao · 1×
Citations per year

Countries citing papers authored by Zhao Jun

Since Specialization
Citations

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

Fields of papers citing papers by Zhao Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201974
2 201960
3 202243
4 201841
5 201640
6 201839
7 202139
8 202335
9 202034
10 202030
11 202425
12 202124
13 202423
14 202421
15 202421
16 201620
17 201419
18 202018
19 201318
20 202417

About Zhao Jun

Zhao Jun is a scholar working on Biomedical Engineering, Mechanical Engineering, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Mechanics of Materials, having authored 87 papers that have together received 875 indexed citations. Recurring topics across this work include Advanced Surface Polishing Techniques (30 papers), Advanced machining processes and optimization (22 papers), Optical measurement and interference techniques (9 papers), Advanced Measurement and Metrology Techniques (9 papers), Statistical Distribution Estimation and Applications (8 papers), Erosion and Abrasive Machining (7 papers), Advanced Machining and Optimization Techniques (7 papers) and Industrial Vision Systems and Defect Detection (5 papers). The work is most often cited by research in Ecological Modeling (134 citations), Mechanical Engineering (485 citations), Biomedical Engineering (562 citations), Computational Mechanics (158 citations) and Computer Vision and Pattern Recognition (94 citations). Zhao Jun has collaborated with scholars based in China, South Korea and United States. Frequent co-authors include Shiming Ji, Cheng Fan, E. Y. Jiang, Wei Hang, Jinfeng Huang, Zhenzhen Chen, Huan Qi, Ji Zhao, Ming Kong and Daodang Wang. Their work appears in journals such as Journal of Manufacturing Processes, Tribology International, Optics Express, The International Journal of Advanced Manufacturing Technology and Precision Engineering.

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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