Mingda Chen

1.9k citations
43 papers · 570 · h-index 13

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Fiber-reinforced polymer composites
    • Advanced machining processes and optimization

Papers in

Mingda Chen

40 papers receiving 544 citations

Peers

Mingda Chen
Comparison fields: 5 of 82
  • Artificial Intelligence 248
  • Mechanical Engineering 192
  • Polymers and Plastics 52
  • Computer Vision and Pattern Recognition 70
  • Mechanics of Materials 69
Replace Chang-Hyun Kim with:
Chang-Hyun Kim South Korea
Yonggang Deng China
Zhibiao Tu China
Liangliang Zhang China
Jingfan Zhang China
Meiling Zhang China
Chengzu Li China
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Mingda Chen relative to Chang-Hyun Kim South Korea Chang-Hyun Kim's profile →
Citations per field
00.5×2×3.5×
Chang-Hyun Kim · 1×
Citations per year

Countries citing papers authored by Mingda Chen

Since Specialization
Citations

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

Fields of papers citing papers by Mingda Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201973
2 202366
3 201947
4 200232
5 202132
6 202231
7 201830
8 202228
9 202124
10 201919
11 202219
12 200417
13 202114
14 202213
15 200211
16 202311
17 202311
18 200510
19 202410
20 20208

About Mingda Chen

Mingda Chen is a scholar working on Artificial Intelligence, Mechanical Engineering, Pharmacology, Information Systems and Mechanics of Materials, having authored 43 papers that have together received 570 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (15 papers), Advanced Surface Polishing Techniques (5 papers), Advanced Machining and Optimization Techniques (4 papers), Advanced machining processes and optimization (4 papers), Musculoskeletal pain and rehabilitation (3 papers), Mechanical Behavior of Composites (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (248 citations), Mechanical Engineering (192 citations), Polymers and Plastics (52 citations), Computer Vision and Pattern Recognition (70 citations) and Mechanics of Materials (69 citations). Mingda Chen has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Kevin Gimpel, Sam Wiseman, Qingming Tang, Yingdan Zhu, Gang Chen, Chun Yan, Hai‐Bing Xu, Wang-Long Li, Guangbin Cai and Dong Liu. Their work appears in journals such as Polymer Composites, The International Journal of Advanced Manufacturing Technology, Tribology International, Ultrasonics and Journal of Applied Polymer Science.

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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