Chong Lv

723 citations
15 papers · 515 · h-index 9

Impact in

Papers in

Chong Lv

12 papers receiving 505 citations

Peers

Chong Lv
Comparison fields: 5 of 41
  • Control and Systems Engineering 238
  • Mechanical Engineering 334
  • Biomedical Engineering 340
  • Industrial and Manufacturing Engineering 72
  • Computer Vision and Pattern Recognition 44
Replace Zhongtao Fu with:
Zhongtao Fu China
Yingjie Guo China
Chao Yun China
Aitor Olarra Spain
Xiaozhi Feng China
Bruce Hazel Canada
Z. Gong Singapore
Zeyuan Yang China
Russell DeVlieg Australia
Hélène Chanal France
Chong Lv relative to Zhongtao Fu China Zhongtao Fu's profile →
Citations per field
00.5×1.5×2.3×
Zhongtao Fu · 1×
Citations per year

Countries citing papers authored by Chong Lv

Since Specialization
Citations

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

Fields of papers citing papers by Chong Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Chong Lv, 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 Chong Lv Line = papers co-authored together Chong Lv links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2021114
2 2016113
3 201685
4 202148
5 202238
6 202233
7 202131
8 202129
9 202412
10 20238
11 20223
12 20241
13 20250
14 20250
15 20250

About Chong Lv

Chong Lv is a scholar working on Mechanical Engineering, Biomedical Engineering, Control and Systems Engineering, Electrical and Electronic Engineering and Industrial and Manufacturing Engineering, having authored 15 papers that have together received 515 indexed citations. Recurring topics across this work include Advanced Surface Polishing Techniques (13 papers), Advanced machining processes and optimization (11 papers), Advanced Measurement and Metrology Techniques (6 papers), Robotic Mechanisms and Dynamics (3 papers), Soft Robotics and Applications (2 papers), Advanced Machining and Optimization Techniques (2 papers), Iterative Learning Control Systems (2 papers) and Optical measurement and interference techniques (1 paper). The work is most often cited by research in Control and Systems Engineering (238 citations), Mechanical Engineering (334 citations), Biomedical Engineering (340 citations), Industrial and Manufacturing Engineering (72 citations) and Computer Vision and Pattern Recognition (44 citations). Chong Lv has collaborated with scholars based in China. Frequent co-authors include Lai Zou, Fengjie Tian, Zhenguo Li, Yun Huang, Yun Huang, Wenxi Wang, Heng Li, Ziling Wang, Lian Duan and Tingting Wang. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, Robotics and Computer-Integrated Manufacturing, Chinese Journal of Aeronautics, Journal of Manufacturing Processes and Aerospace Science and Technology.

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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