Amazon (United States)

4.2k papers and 53.9k indexed citations i.

About

In recent decades, authors affiliated with Amazon (United States) have published 4.2k papers, which have received a total of 53.9k indexed citations. Scholars at this organization have produced 1.3k papers in Artificial Intelligence, 507 papers in Computer Vision and Pattern Recognition and 289 papers in Signal Processing on the topics of Topic Modeling (445 papers), Natural Language Processing Techniques (336 papers) and Speech Recognition and Synthesis (180 papers). Their work is cited by papers focused on Artificial Intelligence (15.8k citations), Computer Vision and Pattern Recognition (8.7k citations) and Global and Planetary Change (4.7k citations). Authors at Amazon (United States) collaborate with scholars in United States, Brazil and United Kingdom and have published in prestigious journals including Nature, Science and Proceedings of the National Academy of Sciences. Some of Amazon (United States)'s most productive authors include Philip M. Fearnside, Ross C. Walker, Andreas W. Götz, Ghillean Τ. Prance, Adalberto Luís Val, Stefano Soatto, Avinash Ravichandran, Hang Zhang, Adrián E. Roitberg and Yonina C. Eldar.

In The Last Decade

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Amazon (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 Amazon (United States) at the time of their publication.

Countries citing scholars working at Amazon (United States)

Since Specialization

Citations

This map shows the geographic impact of research produced by authors working at Amazon (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 Amazon (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 Amazon (United States) 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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