Jake Bouvrie

35 total papers · 766 total citations
14 papers, 517 citations indexed

About

Jake Bouvrie is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jake Bouvrie has authored 14 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Signal Processing, 6 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jake Bouvrie's work include Speech and Audio Processing (5 papers), Music and Audio Processing (4 papers) and Blind Source Separation Techniques (4 papers). Jake Bouvrie is often cited by papers focused on Speech and Audio Processing (5 papers), Music and Audio Processing (4 papers) and Blind Source Separation Techniques (4 papers). Jake Bouvrie collaborates with scholars based in United States and Lebanon. Jake Bouvrie's co-authors include Tomaso Poggio, Tony Ezzat, Maxim Raginsky, Lorenzo Rosasco, Pawan Sinha, Ryan Rifkin, Jean-Jacques Slotine, Minjoon Kouh, Mauro Maggioni and Andre Wibisono and has published in prestigious journals such as Neural Computation, Neurocomputing and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Jake Bouvrie

14 papers receiving 485 citations

Author Peers

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

Author Last Decade Papers Cites
Jake Bouvrie 174 157 151 50 35 14 517
George Sebestyen 287 1.6× 89 0.6× 162 1.1× 20 0.4× 29 0.8× 16 584
Anupriya Gogna 218 1.3× 71 0.5× 135 0.9× 59 1.2× 24 0.7× 15 611
Rabia Bakhteri 101 0.6× 182 1.2× 217 1.4× 19 0.4× 16 0.5× 21 491
Yi Lu 166 1.0× 76 0.5× 90 0.6× 19 0.4× 17 0.5× 14 501
Hong He 165 0.9× 89 0.6× 195 1.3× 123 2.5× 16 0.5× 35 551
Giorgio Roffo 223 1.3× 44 0.3× 161 1.1× 52 1.0× 20 0.6× 17 491
Wen-Hoar Hsaio 302 1.7× 120 0.8× 122 0.8× 73 1.5× 9 0.3× 10 540
Luisa F. Polanía 78 0.4× 171 1.1× 171 1.1× 44 0.9× 22 0.6× 24 587
R. C. Kemerait 94 0.5× 163 1.0× 103 0.7× 28 0.6× 18 0.5× 5 513
Yuki Yamaguchi 195 1.1× 250 1.6× 147 1.0× 36 0.7× 9 0.3× 21 596

Countries citing papers authored by Jake Bouvrie

Since Specialization
Citations

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

Fields of papers citing papers by Jake Bouvrie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jake Bouvrie

This figure shows the co-authorship network connecting the top 25 collaborators of Jake Bouvrie. A scholar is included among the top collaborators of Jake Bouvrie 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 Jake Bouvrie. Jake Bouvrie 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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