Mei Chen

2.6k total citations · 1 hit paper
87 papers, 1.8k citations indexed

About

Mei Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Atmospheric Science. According to data from OpenAlex, Mei Chen has authored 87 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 12 papers in Atmospheric Science. Recurrent topics in Mei Chen's work include Air Quality and Health Impacts (10 papers), AI in cancer detection (10 papers) and Atmospheric chemistry and aerosols (9 papers). Mei Chen is often cited by papers focused on Air Quality and Health Impacts (10 papers), AI in cancer detection (10 papers) and Atmospheric chemistry and aerosols (9 papers). Mei Chen collaborates with scholars based in China, United States and Australia. Mei Chen's co-authors include Weidong Cai, Dagan Feng, Yun Zhou, Qing Li, Xiaogang Wang, Yang Song, Heng Huang, Songjun Guo, Afaf Tareef and Jihua Tan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Journal of Agricultural and Food Chemistry.

In The Last Decade

Mei Chen

78 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Medical image classification with convolutional neural network

2014 553 citations Weidong Cai, Dagan Feng et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mei Chen China	22	739	508	302	184	172	87	1.8k
Pin Wang China	21	809 1.1×	559 1.1×	429 1.4×	49 0.3×	267 1.6×	170	2.3k
Huimin Huang China	16	649 0.9×	1.0k 2.0×	571 1.9×	68 0.4×	282 1.6×	71	2.5k
Alberto García-García Spain	15	421 0.6×	1.1k 2.2×	183 0.6×	24 0.1×	165 1.0×	34	2.6k
M. A. Ganaie India	20	988 1.3×	610 1.2×	212 0.7×	28 0.2×	147 0.9×	40	2.4k
Haopeng Zhang China	31	726 1.0×	1.2k 2.4×	241 0.8×	28 0.2×	434 2.5×	189	2.9k
Sebastian Lapuschkin Germany	16	1.6k 2.2×	610 1.2×	231 0.8×	18 0.1×	145 0.8×	34	2.8k
Jinshan Tang United States	32	1.2k 1.6×	1.7k 3.3×	1.1k 3.5×	25 0.1×	405 2.4×	154	3.6k
Farhad Pourpanah China	20	1.3k 1.8×	627 1.2×	243 0.8×	12 0.1×	147 0.9×	37	2.9k
Sebastian Bach South Korea	2	1.6k 2.2×	468 0.9×	218 0.7×	22 0.1×	85 0.5×	2	2.5k

Countries citing papers authored by Mei Chen

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Chen, Mei, et al.. (2025). Core Triangle Motif-Driven Local Community Detection Algorithm. IEEE Transactions on Computational Social Systems. 12(6). 4401–4412.

2.

Fan, Jing‐Wei, Mei Chen, Fuping Tian, et al.. (2025). Root morphology, exudate patterns, and mycorrhizal symbiosis are determinants to improve phosphorus acquisition in alfalfa. Journal of Experimental Botany. 76(12). 3543–3559. 4 indexed citations

3.

Wang, Dong, Mengjie Zhang, Xiaoyang Zhu, et al.. (2025). Multimaterial 3D printed soft robots with embedded actuation and sensing. Science Advances. 11(51). eadz2928–eadz2928.

4.

Chen, Mei, et al.. (2024). Density change consistency clustering from density extreme. Pattern Recognition. 158. 110932–110932. 2 indexed citations

5.

Chen, Mei, et al.. (2024). Consensus Multi-view subspace clustering based on Graph Filtering. Neurocomputing. 591. 127742–127742. 3 indexed citations

6.

Chen, Mei, Xin Fang, Ying‐Bo Mao, et al.. (2024). Regulation of Glandular Size and Phytoalexin Biosynthesis by a Negative Feedback Loop in Cotton. Advanced Science. 11(30). e2403059–e2403059. 7 indexed citations

7.

Qin, Jing‐Kai, et al.. (2024). Evaluation of High Vacuum Flavor Extraction Device as a Novel Technique for the Extraction of Volatile Compounds. Foods. 13(19). 3206–3206.

8.

Tang, Xu, Mei Chen, Jun He, et al.. (2020). Synthesis and biological activity of 1,4-pentadien-3-one derivatives containing triazine scaffolds. 2. e3–e3. 2 indexed citations

9.

Chen, Mei, et al.. (2019). Effectively Detecting Communities by Adjusting Initial Structure via Cores. Complexity. 2019(1). 3 indexed citations

10.

Li, Hui, et al.. (2019). Taxi Abnormal Trajectory Detection Based on Density Clustering. Computer and Modernization. 49.

11.

Tareef, Afaf, Yang Song, Heng Huang, et al.. (2018). Multi-Pass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells. IEEE Transactions on Medical Imaging. 37(9). 2044–2059. 76 indexed citations

12.

Tareef, Afaf, Yang Song, Heng Huang, et al.. (2017). Optimizing the cervix cytological examination based on deep learning and dynamic shape modeling. Neurocomputing. 248. 28–40. 53 indexed citations

13.

Su, Yuting, et al.. (2017). Spatiotemporal Joint Mitosis Detection Using CNN-LSTM Network in Time-Lapse Phase Contrast Microscopy Images. IEEE Access. 5. 18033–18041. 39 indexed citations

14.

Chen, Mei, et al.. (2017). The application of intelligent control algorithm in sanitation monitoring system. 259–263. 2 indexed citations

15.

Wen, Aijun, et al.. (2016). A Photonic Technique for Instantaneous Microwave Frequency Measurement Utilizing a Phase Modulator. IEEE Photonics Technology Letters. 28(24). 2795–2798. 27 indexed citations

16.

Tareef, Afaf, Yang Song, Weidong Cai, et al.. (2016). Automatic segmentation of overlapping cervical smear cells based on local distinctive features and guided shape deformation. Neurocomputing. 221. 94–107. 52 indexed citations

17.

Guo, Songjun, et al.. (2014). Photochemical Production of Atmospheric Carbonyls in a Rural Area in Southern China. Archives of Environmental Contamination and Toxicology. 66(4). 594–605. 19 indexed citations

18.

Yin, Zhaozheng, Kang Li, Takeo Kanade, & Mei Chen. (2010). Understanding the Optics to Aid Microscopy Image Segmentation. Lecture notes in computer science. 13(Pt 1). 209–217. 43 indexed citations

19.

Chen, Mei. (2008). Formation of Multi-Objective Dynamic Cells Using Random Weight Multi-Objective Genetic Algorithm. Guanli xuebao. 1 indexed citations

20.

Chen, Mei & Feng Liu. (2003). A Texture Recognition Technology Based on Neural Network. 20(4). 400–406. 1 indexed citations

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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