Ming Luo

3.8k total citations · 1 hit paper
154 papers, 2.8k citations indexed

About

Ming Luo is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Ming Luo has authored 154 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 122 papers in Mechanical Engineering, 63 papers in Biomedical Engineering and 58 papers in Electrical and Electronic Engineering. Recurrent topics in Ming Luo's work include Advanced machining processes and optimization (103 papers), Advanced Surface Polishing Techniques (59 papers) and Advanced Machining and Optimization Techniques (55 papers). Ming Luo is often cited by papers focused on Advanced machining processes and optimization (103 papers), Advanced Surface Polishing Techniques (59 papers) and Advanced Machining and Optimization Techniques (55 papers). Ming Luo collaborates with scholars based in China, Hong Kong and United Kingdom. Ming Luo's co-authors include Dinghua Zhang, Baohai Wu, Baohai Wu, Kai Tang, Pei Wang, Dongsheng Liu, Chenwei Shan, Jia‐Wei Mei, Zhao Zhang and Minchao Cui and has published in prestigious journals such as Journal of Cleaner Production, ACS Applied Materials & Interfaces and IEEE Transactions on Power Electronics.

In The Last Decade

Ming Luo

144 papers receiving 2.7k citations

Hit Papers

Comparative study on machinability and surface integrity ... 2024 2026 2025 2024 20 40 60

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ming Luo China 31 2.3k 1.1k 907 892 367 154 2.8k
Panorios Benardos Greece 13 1.4k 0.6× 527 0.5× 756 0.8× 592 0.7× 246 0.7× 34 1.9k
Victor Songméné Canada 27 2.1k 0.9× 863 0.8× 1.0k 1.1× 419 0.5× 103 0.3× 182 2.5k
Choon-Man Lee South Korea 30 2.2k 0.9× 819 0.7× 1.0k 1.1× 312 0.3× 385 1.0× 180 2.7k
Klaus Weinert Germany 24 3.1k 1.4× 1.8k 1.6× 1.4k 1.6× 645 0.7× 307 0.8× 81 3.7k
Garret E. O’Donnell Ireland 26 2.4k 1.0× 882 0.8× 886 1.0× 717 0.8× 114 0.3× 75 3.2k
Beizhi Li China 28 1.8k 0.8× 1.4k 1.2× 596 0.7× 293 0.3× 124 0.3× 107 2.2k
J.A. Sánchez Spain 38 4.0k 1.8× 2.3k 2.1× 2.3k 2.6× 871 1.0× 488 1.3× 147 4.5k
Stanisław Legutko Poland 31 2.4k 1.0× 741 0.7× 845 0.9× 500 0.6× 198 0.5× 165 3.3k
Doriana M. D’Addona Italy 23 1.2k 0.5× 528 0.5× 656 0.7× 550 0.6× 118 0.3× 88 1.7k
Byung-Kwon Min South Korea 23 911 0.4× 694 0.6× 681 0.8× 447 0.5× 145 0.4× 80 1.9k

Countries citing papers authored by Ming Luo

Since Specialization
Citations

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

Fields of papers citing papers by Ming Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Luo. A scholar is included among the top collaborators of Ming Luo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Luo. Ming Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Chong, Zhidong Li, Ji Zhang, et al.. (2025). FlowerBase: An integrated multi-omics database for ornamental flowering plants. Plant Communications. 7(1). 101565–101565. 1 indexed citations
2.
Xue, Dongfeng, et al.. (2025). Grinding force and surface quality of ultrasonic-assisted grinding needle-punched C/C composites. The International Journal of Advanced Manufacturing Technology. 137(1-2). 411–427. 1 indexed citations
3.
Tan, Liang, Minchao Cui, Junxue Ren, et al.. (2025). Research progress on intelligent monitoring of machining condition based on indirect method. Advanced Engineering Informatics. 67. 103518–103518.
4.
Luo, Ming, et al.. (2024). Extreme learning machine oriented surface roughness prediction at continuous cutting positions based on monitored acceleration. Mechanical Systems and Signal Processing. 219. 111633–111633. 12 indexed citations
5.
Ma, Junjun, et al.. (2024). Research on spatial corrosion behavior and durability protection technology of concrete box girder bridge in cold regions. Construction and Building Materials. 441. 137585–137585. 3 indexed citations
6.
Luo, Ming, et al.. (2024). A strategy to reduce spectral intensity uncertainty and predicted content uncertainty of low and medium alloy steel elements. Spectrochimica Acta Part B Atomic Spectroscopy. 215. 106919–106919. 2 indexed citations
7.
Yang, Nan, et al.. (2024). Combination of plasma acoustic emission signal and laser-induced breakdown spectroscopy for accurate classification of steel. Analytica Chimica Acta. 1336. 343496–343496. 36 indexed citations
8.
Cui, Minchao, et al.. (2024). Comparative study on machinability and surface integrity of γ-TiAl alloy in laser assisted milling. Journal of Materials Research and Technology. 33. 3743–3755. 70 indexed citations breakdown →
9.
Shan, Chenwei, et al.. (2024). Dynamic mechanical model in grinding C/SiC composites. International Journal of Mechanical Sciences. 268. 109042–109042. 32 indexed citations
10.
Zhang, Zhao, et al.. (2024). A data-driven method for prediction of surface roughness with consideration of milling tool wear. The International Journal of Advanced Manufacturing Technology. 134(9-10). 4271–4282. 2 indexed citations
11.
Zhang, Menghua, Chenwei Shan, Ziwen Xia, Ming Luo, & Dinghua Zhang. (2023). Scratch-induced surface formation mechanism in C/SiC composites. International Journal of Mechanical Sciences. 265. 108885–108885. 24 indexed citations
12.
Luo, Ming, et al.. (2023). Study on the cutting force responses in machining multiscale carbon nanotube/carbon fiber reinforced polymer composites. Journal of Manufacturing Processes. 95. 160–170. 1 indexed citations
13.
Zhang, Zhao, et al.. (2023). Research on tool wear modeling of superalloy based on evolutionary cluster analysis. The International Journal of Advanced Manufacturing Technology. 129(1-2). 143–166. 6 indexed citations
14.
Li, Jing, et al.. (2023). In-situ study of damage mechanisms in Mg–6Li dual-phase alloy. Journal of Material Science and Technology. 179. 114–124. 12 indexed citations
15.
Wu, Ming, et al.. (2023). Position-dependent milling process monitoring and surface roughness prediction for complex thin-walled blade component. Mechanical Systems and Signal Processing. 198. 110439–110439. 27 indexed citations
18.
Luo, Ming, Jing Wang, Baohai Wu, & Dinghua Zhang. (2017). Effects of cutting parameters on tool insert wear in end milling of titanium alloy Ti6Al4V. Chinese Journal of Mechanical Engineering. 30(1). 53–59. 26 indexed citations
19.
Luo, Ming. (2010). Influencing factors of the Carboniferous volcanic reservoirs in Beisantai area of east Junggar Basin. Special Oil & Gas Reservoirs. 1 indexed citations
20.
Luo, Ming. (2000). Defects for Upward Rock Deformation Observation Instrument during Grouting and Improvement.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026