Mingda Chen
Impact in
- Mechanical Engineering top 10%
- Fiber-reinforced polymer composites
- Advanced machining processes and optimization
- Tribology and Lubrication Engineering
Papers in
-
- Natural Language Processing Techniques 10
- Topic Modeling 9
-
- Advanced machining processes and optimization 4
- Co-authors
- Yingdan Zhu (11 shared papers)Gang Chen (10 shared papers)Kevin Gimpel (8 shared papers)Chun Yan (4 shared papers)Wang-Long Li (3 shared papers)Hai‐Bing Xu (3 shared papers)Dong Liu (2 shared papers)Guangbin Cai (2 shared papers)
- Journals
- Polymer Composites (3 papers)Tribology International (2 papers)Ultrasonics (2 papers)The International Journal of Advanced Manufacturing Technology (2 papers)Advanced Engineering Informatics (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Mingda Chen
34 papers receiving 370 citations
Peers
Comparison fields: 5 of 73
- Mechanical Engineering 187
- Polymers and Plastics 50
- Artificial Intelligence 90
- Mechanics of Materials 68
- Biomedical Engineering 64
Countries citing papers authored by Mingda Chen
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
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.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 61 | |
| 2 | 2002 | 32 | |
| 3 | 2022 | 30 | |
| 4 | 2021 | 29 | |
| 5 | 2022 | 27 | |
| 6 | 2021 | 23 | |
| 7 | 2018 | 20 | |
| 8 | 2004 | 17 | |
| 9 | 2022 | 17 | |
| 10 | 2021 | 12 | |
| 11 | 2023 | 11 | |
| 12 | 2002 | 11 | |
| 13 | 2005 | 10 | |
| 14 | 2023 | 10 | |
| 15 | 2022 | 10 | |
| 16 | 2020 | 8 | |
| 17 | 2024 | 7 | |
| 18 | 2023 | 6 | |
| 19 | 2019 | 6 | |
| 20 | 2020 | 5 |
About Mingda Chen
Mingda Chen is a scholar working on Artificial Intelligence, Mechanical Engineering, Biomedical Engineering, Surgery and Pharmacology, having authored 36 papers that have together received 382 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (9 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 Wikis in Education and Collaboration (2 papers). The work is most often cited by research in Mechanical Engineering (187 citations), Polymers and Plastics (50 citations), Artificial Intelligence (90 citations), Mechanics of Materials (68 citations) and Biomedical Engineering (64 citations). Mingda Chen has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Yingdan Zhu, Gang Chen, Kevin Gimpel, Chun Yan, Wang-Long Li, Hai‐Bing Xu, Dong Liu, Guangbin Cai, Sam Wiseman and Dongxi Lv. Their work appears in journals such as Polymer Composites, Tribology International, Ultrasonics, The International Journal of Advanced Manufacturing Technology and Advanced Engineering Informatics.
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.