Mingchun Liu

1.1k citations
22 papers · 814 indexed · h-index 12
Topics
Vehicle Dynamics and Control Systems (10 papers)Electric and Hybrid Vehicle Technologies (6 papers)Advanced Battery Technologies Research (4 papers)

In The Last Decade

Mingchun Liu

20 papers receiving 786 citations

Peers

Mingchun Liu
Comparison fields: 5 of 59
  • Automotive Engineering 618
  • Electrical and Electronic Engineering 448
  • Mechanical Engineering 256
  • Control and Systems Engineering 131
  • Civil and Structural Engineering 107
Replace Shaoyi Bei with:
Shaoyi Bei China
Cong Geng China
Haitao Min China
Lin He China
Angelo Bonfitto Italy
Amit Bhattacharjee United States
Jong‐Seob Won South Korea
Hyun-Rok Cha South Korea
M. Balaji India
Yuzhuang Zhao China
Mingchun Liu relative to Shaoyi Bei China Shaoyi Bei's profile →
Citations per field
00.5×5.2×
Shaoyi Bei · 1×
Citations per year

Countries citing papers authored by Mingchun Liu

Since Specialization
Citations

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

Fields of papers citing papers by Mingchun Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingchun Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Mingchun Liu. A scholar is included among the top collaborators of Mingchun Liu 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 Mingchun Liu. Mingchun Liu 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
#WorkIndexed citations
1 2
2 1
3 26
4 3
5 3
6 78
7 35
8 18
9 6
10 16
11 50
12 63
13 157
14 43
15 262
16 2
17 6
18 0
19
Boolean Search for Content-Based Retrieval using Fuzzy Logic.
0
20 13

About Mingchun Liu

Mingchun Liu is a scholar working on Automotive Engineering, Signal Processing and Computer Vision and Pattern Recognition, having authored 22 papers that have together received 814 indexed citations. Recurring topics across this work include Vehicle Dynamics and Control Systems (10 papers), Electric and Hybrid Vehicle Technologies (6 papers) and Advanced Battery Technologies Research (4 papers). The work is most often cited by research in Automotive Engineering (618 citations), Electrical and Electronic Engineering (448 citations) and Mechanical Engineering (256 citations). Mingchun Liu has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Juhua Huang, Ming Cao, Guiwen Jiang, Yanshu Fu, Yuanzhi Zhang, Caizhi Zhang, Chunru Wan, Lei Zhang, Zhenpo Wang and Zhiyu Huang. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Applied Thermal 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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