Minming Chen
Impact in
- Computational Mathematics top 5%
- Tensor decomposition and applications
- Computational Mechanics top 5%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Invertebrate Immune Response Mechanisms 3
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- Sparse and Compressive Sensing Techniques 2
- Co-authors
- John N. Wright (2 shared papers)Yi Ma (2 shared papers)Arvind Ganesh (2 shared papers)Zhouchen Lin (2 shared papers)Leqin Wu (2 shared papers)Jing Hong (1 shared paper)Pei Hu (1 shared paper)Taotao Chen (1 shared paper)
- Journals
- Frontiers in Pediatrics (1 paper)The Journal of Immunology (1 paper)International Journal of Molecular Sciences (1 paper)Medicine (1 paper)Phlebology The Journal of Venous Disease (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Minming Chen
9 papers receiving 579 citations
Minming Chen's Hit Papers
Peers
Comparison fields: 5 of 60
- Computational Mathematics 21
- Computational Mechanics 205
- Computer Vision and Pattern Recognition 192
- Signal Processing 14
- Artificial Intelligence 56
Countries citing papers authored by Minming Chen
This map shows the geographic impact of Minming 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 Minming Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minming Chen more than expected).
Fields of papers citing papers by Minming Chen
This network shows the impact of papers produced by Minming 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 Minming Chen. The network helps show where Minming Chen may publish in the future.
Co-authors
The 22 scholars most cited alongside Minming 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
| # | Work | ||
|---|---|---|---|
| 1 | Fast Convex Optimization Algorithms for Exact Recovery of a Corrupted Low-Rank Matrix Hit paper breakdown → | 2009 | 369 |
| 2 | 2009 | 169 | |
| 3 | 2018 | 31 | |
| 4 | 2018 | 11 | |
| 5 | 2022 | 8 | |
| 6 | 2020 | 7 | |
| 7 | 2025 | 2 | |
| 8 | 2019 | 1 | |
| 9 | 2023 | 1 |
About Minming Chen
Minming Chen is a scholar working on Immunology, Computational Mechanics, Nutrition and Dietetics, Surgery and Molecular Biology, having authored 9 papers that have together received 599 indexed citations. Recurring topics across this work include Invertebrate Immune Response Mechanisms (3 papers), Sparse and Compressive Sensing Techniques (2 papers), Protein Hydrolysis and Bioactive Peptides (1 paper), Congenital gastrointestinal and neural anomalies (1 paper), Vascular anomalies and interventions (1 paper) and Infant Nutrition and Health (1 paper). The work is most often cited by research in Computational Mathematics (21 citations), Computational Mechanics (205 citations), Computer Vision and Pattern Recognition (192 citations), Signal Processing (14 citations) and Artificial Intelligence (56 citations). Minming Chen has collaborated with scholars based in China and United States. Frequent co-authors include John N. Wright, Yi Ma, Arvind Ganesh, Zhouchen Lin, Leqin Wu, Jing Hong, Pei Hu, Taotao Chen, Yanjie Liu and Shaoyun Wang. Their work appears in journals such as Frontiers in Pediatrics, The Journal of Immunology, International Journal of Molecular Sciences, Medicine and Phlebology The Journal of Venous Disease.
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.