Mei Chen
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Health, Toxicology and Mutagenesis top 5%
- Biomedical Engineering
- Topics
- Air Quality and Health Impacts (10 papers)AI in cancer detection (10 papers)Atmospheric chemistry and aerosols (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaEnvironmental Science & TechnologyJournal of Agricultural and Food Chemistry
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Mei Chen
78 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Artificial Intelligence 739
- Computer Vision and Pattern Recognition 508
- Radiology, Nuclear Medicine and Imaging 302
- Health, Toxicology and Mutagenesis 184
- Biomedical Engineering 172
Countries citing papers authored by Mei Chen
This map shows the geographic impact of Mei 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 Mei Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mei Chen more than expected).
Fields of papers citing papers by Mei Chen
This network shows the impact of papers produced by Mei 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 Mei Chen. The network helps show where Mei Chen may publish in the future.
Co-authorship network of co-authors of Mei Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Mei Chen. A scholar is included among the top collaborators of Mei Chen 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 Mei Chen. Mei Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 0 | |
| 11 | 76 | |
| 12 | 53 | |
| 13 | 39 | |
| 14 | 2 | |
| 15 | 27 | |
| 16 | 52 | |
| 17 | 19 | |
| 18 | 43 | |
| 19 | Formation of Multi-Objective Dynamic Cells Using Random Weight Multi-Objective Genetic Algorithm | 1 |
| 20 | A Texture Recognition Technology Based on Neural Network | 1 |
About Mei Chen
Mei Chen is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Health, Toxicology and Mutagenesis, having authored 87 papers that have together received 1.8k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (10 papers), AI in cancer detection (10 papers) and Atmospheric chemistry and aerosols (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (508 citations), Artificial Intelligence (739 citations) and Biophysics (116 citations). Mei Chen has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Weidong Cai, Dagan Feng, Yun Zhou, Qing Li, Xiaogang Wang, Yang Song, Heng Huang, Songjun Guo, Afaf Tareef and Jihua Tan. Their work appears in journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology 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.