Brooks Paige

96 total papers · 1.9k total citations
26 papers, 505 citations indexed

About

Brooks Paige is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Atmospheric Science. According to data from OpenAlex, Brooks Paige has authored 26 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 5 papers in Atmospheric Science. Recurrent topics in Brooks Paige's work include Machine Learning in Materials Science (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Computational Drug Discovery Methods (4 papers). Brooks Paige is often cited by papers focused on Machine Learning in Materials Science (5 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Computational Drug Discovery Methods (4 papers). Brooks Paige collaborates with scholars based in United Kingdom, United States and Germany. Brooks Paige's co-authors include Chris Russell, Stephen Law, N. Siddharth, Philip H. S. Torr, Andrew Elliott, Daniel C. Jones, Emily Shuckburgh, Rod Downie, Tom R. Andersson and Beena Balan Sarojini and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Brooks Paige

26 papers receiving 487 citations

Hit Papers

Seasonal Arctic sea ice f... 2021 2026 2022 2024 2021 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Brooks Paige 126 114 106 91 50 26 505
中国科学院 33 0.3× 32 0.3× 59 0.6× 33 0.4× 29 0.6× 20 506
Chao He 41 0.3× 97 0.9× 27 0.3× 29 0.3× 25 0.5× 47 505
Yu-Ting Cheng 110 0.9× 77 0.7× 69 0.7× 57 0.6× 24 0.5× 25 602
Sebastian Böcker 47 0.4× 55 0.5× 66 0.6× 27 0.3× 22 0.4× 18 562
Xiaochi Zhou 101 0.8× 197 1.7× 87 0.8× 14 0.2× 12 0.2× 23 510
Jun Yu 59 0.5× 30 0.3× 139 1.3× 39 0.4× 17 0.3× 50 605
Thomas Austin 30 0.2× 43 0.4× 27 0.3× 16 0.2× 27 0.5× 45 572
Hanfang Yang 32 0.3× 84 0.7× 88 0.8× 69 0.8× 127 2.5× 33 556
Ruiyang Liu 63 0.5× 56 0.5× 72 0.7× 102 1.1× 148 3.0× 38 612
Hailing Xiong 22 0.2× 50 0.4× 100 0.9× 120 1.3× 16 0.3× 62 569

Countries citing papers authored by Brooks Paige

Since Specialization
Citations

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

Fields of papers citing papers by Brooks Paige

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brooks Paige

This figure shows the co-authorship network connecting the top 25 collaborators of Brooks Paige. A scholar is included among the top collaborators of Brooks Paige 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 Brooks Paige. Brooks Paige is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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