Лей Ма

127 papers and 950 indexed citations i.

About

Лей Ма is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Лей Ма has authored 127 papers receiving a total of 950 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 18 papers in Electrical and Electronic Engineering and 18 papers in Artificial Intelligence. Recurrent topics in Лей Ма’s work include Influenza Virus Research Studies (13 papers), Viral gastroenteritis research and epidemiology (11 papers) and Quantum Information and Cryptography (9 papers). Лей Ма is often cited by papers focused on Influenza Virus Research Studies (13 papers), Viral gastroenteritis research and epidemiology (11 papers) and Quantum Information and Cryptography (9 papers). Лей Ма collaborates with scholars based in China, United States and Hong Kong. Лей Ма's co-authors include Yun Li, Guoxiang Huang, Chao Hang, Yang Liu, Tiejun Huang, Yundong Zhang, Ping Yuan, Kang Hao Cheong, Chao Wang and Jin‐Ming Liu and has published in prestigious journals such as Advanced Materials, Nature Communications and Journal of Applied Physics.

In The Last Decade

Co-authorship network of co-authors of Лей Ма i

Fields of papers citing papers by Лей Ма

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Лей Ма. 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 Лей Ма. The network helps show where Лей Ма may publish in the future.

Countries citing papers authored by Лей Ма

Since Specialization
Citations

This map shows the geographic impact of Лей Ма'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 Лей Ма with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Лей Ма more than expected).

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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2025