Microsoft (United States)

21.1k papers and 1.2M indexed citations

About

In recent decades, authors affiliated with Microsoft (United States) have published 21.1k papers, which have received a total of 1.2M indexed citations. Scholars at this organization have produced 7.0k papers in Artificial Intelligence, 4.7k papers in Computer Networks and Communications and 4.1k papers in Information Systems on the topics of Topic Modeling (1.4k papers), Natural Language Processing Techniques (1.1k papers) and Parallel Computing and Optimization Techniques (1.0k papers). Their work is cited by papers focused on Computer Vision and Pattern Recognition (348.2k citations), Artificial Intelligence (335.4k citations) and Computer Networks and Communications (226.1k citations). Authors at Microsoft (United States) collaborate with scholars in United States, United Kingdom and China and have published in prestigious journals including Nature, Science and New England Journal of Medicine. Some of Microsoft (United States)'s most productive authors include Ross Girshick, Kaiming He, Shaoqing Ren, Jian Sun, Zheng Zhang, Richard Szeliski, Paul Viola, Zhengyou Zhang, Eric Horvitz and Michael Jones.

In The Last Decade

Microsoft (United States)

19.8k papers receiving 1.1M citations

Countries citing scholars working at Microsoft (United States)

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Microsoft (United States). 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 papers produced at Microsoft (United States) with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Microsoft (United States) more than expected).

Fields of papers published by authors at Microsoft (United States)

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Microsoft (United States) at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Microsoft (United States) at the time of their publication.

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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2026