Mingyu Jin
Impact in
- Food Science top 10%
- Polysaccharides Composition and Applications
- Probiotics and Fermented Foods
- Proteins in Food Systems
Papers in
- Food Science 10
- Polysaccharides Composition and Applications 8
- Proteins in Food Systems 4
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- Topic Modeling 6
- Adversarial Robustness in Machine Learning 4
- Natural Language Processing Techniques 4
- Co-authors
- Xiaoyong Wu (4 shared papers)Zhen-Lin Xu (4 shared papers)Yuanming Sun (3 shared papers)Meiying Li (3 shared papers)Hui Yin (1 shared paper)Yuxiao Wang (1 shared paper)Xiaobing Yang (1 shared paper)Shao-Ping Nie (1 shared paper)
- Journals
- Food Chemistry (5 papers)International Journal of Biological Macromolecules (3 papers)Food Hydrocolloids (3 papers)Foods (2 papers)Journal of Agricultural and Food Chemistry (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Mingyu Jin
53 papers receiving 661 citations
Peers
Comparison fields: 5 of 122
- Food Science 140
- Health Informatics 10
- Toxicology 22
- Complementary and alternative medicine 49
- Nutrition and Dietetics 86
Countries citing papers authored by Mingyu Jin
This map shows the geographic impact of Mingyu Jin'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 Mingyu Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyu Jin more than expected).
Fields of papers citing papers by Mingyu Jin
This network shows the impact of papers produced by Mingyu Jin. 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 Mingyu Jin. The network helps show where Mingyu Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingyu Jin, 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 64 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 130 | |
| 2 | 2018 | 109 | |
| 3 | 2021 | 50 | |
| 4 | 2021 | 33 | |
| 5 | 2024 | 30 | |
| 6 | 2024 | 26 | |
| 7 | 2023 | 24 | |
| 8 | 2023 | 24 | |
| 9 | 2024 | 21 | |
| 10 | 2024 | 18 | |
| 11 | 2025 | 16 | |
| 12 | 2022 | 14 | |
| 13 | 2025 | 13 | |
| 14 | 2024 | 11 | |
| 15 | 2016 | 11 | |
| 16 | 2024 | 9 | |
| 17 | 2024 | 9 | |
| 18 | 2017 | 9 | |
| 19 | 2025 | 8 | |
| 20 | 2018 | 8 |
About Mingyu Jin
Mingyu Jin is a scholar working on Food Science, Artificial Intelligence, Nutrition and Dietetics, Plant Science and Computer Vision and Pattern Recognition, having authored 64 papers that have together received 683 indexed citations. Recurring topics across this work include Polysaccharides and Plant Cell Walls (10 papers), Polysaccharides Composition and Applications (8 papers), Topic Modeling (6 papers), Microbial Metabolites in Food Biotechnology (5 papers), Adversarial Robustness in Machine Learning (4 papers), Advanced Neural Network Applications (4 papers), Natural Language Processing Techniques (4 papers) and Proteins in Food Systems (4 papers). The work is most often cited by research in Food Science (140 citations), Health Informatics (10 citations), Toxicology (22 citations), Complementary and alternative medicine (49 citations) and Nutrition and Dietetics (86 citations). Mingyu Jin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaoyong Wu, Zhen-Lin Xu, Yuanming Sun, Meiying Li, Hui Yin, Yuxiao Wang, Xiaobing Yang, Shao-Ping Nie, Jing‐Kun Yan and Long‐Qing Li. Their work appears in journals such as Food Chemistry, International Journal of Biological Macromolecules, Food Hydrocolloids, Foods and Journal of Agricultural and Food Chemistry.
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.