Digital Science (United States)

320 papers and 6.8k indexed citations i.

About

In recent decades, authors affiliated with Digital Science (United States) have published 320 papers, which have received a total of 6.8k indexed citations. Scholars at this organization have produced 45 papers in Artificial Intelligence, 42 papers in Information Systems and 36 papers in Computer Networks and Communications on the topics of Data Management and Algorithms (12 papers), Parallel Computing and Optimization Techniques (9 papers) and Cloud Computing and Resource Management (9 papers). Their work is cited by papers focused on Computer Vision and Pattern Recognition (1.8k citations), Signal Processing (1.6k citations) and Information Systems (1.2k citations). Authors at Digital Science (United States) collaborate with scholars in United States, China and Singapore and have published in prestigious journals including Nature, Journal of the American Chemical Society and JAMA. Some of Digital Science (United States)'s most productive authors include S. Prabhakar, Arun Ross, Anil K. Jain, Zhenjie Zhang, Ming‐Ming Cheng, Yun Liu, Kai Wang, Xiang Bai, Xiaowei Hu and Amy Brand.

In The Last Decade

Fields of papers published by authors at Digital Science (United States)

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing scholars working at Digital Science (United States)

Since Specialization

Citations

This map shows the geographic impact of research produced by authors working at Digital Science (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 Digital Science (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 Digital Science (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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