Jacob S. Prince

43 total papers · 1.1k total citations
17 papers, 348 citations indexed

About

Jacob S. Prince is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Jacob S. Prince has authored 17 papers receiving a total of 348 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Cognitive Neuroscience, 7 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in Jacob S. Prince's work include Face Recognition and Perception (9 papers), Visual perception and processing mechanisms (6 papers) and Neural dynamics and brain function (6 papers). Jacob S. Prince is often cited by papers focused on Face Recognition and Perception (9 papers), Visual perception and processing mechanisms (6 papers) and Neural dynamics and brain function (6 papers). Jacob S. Prince collaborates with scholars based in United States, Canada and United Kingdom. Jacob S. Prince's co-authors include Kendrick Kay, Ian Charest, Franco Pestilli, Matthias Nau, Thomas Naselaris, Yihan Wu, Emily Allen, Logan T. Dowdle, Ben Hutchinson and Ghislain St-Yves and has published in prestigious journals such as Nature Communications, Nature Neuroscience and Scientific Reports.

In The Last Decade

Jacob S. Prince

16 papers receiving 346 citations

Hit Papers

A massive 7T fMRI dataset... 2021 2026 2022 2024 2021 50 100 150 200

Author Peers

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

Author Last Decade Papers Cites
Jacob S. Prince 261 72 33 30 26 17 348
Yihan Wu 220 0.8× 60 0.8× 29 0.9× 41 1.4× 45 1.7× 24 344
N. Apurva Ratan Murty 304 1.2× 81 1.1× 10 0.3× 34 1.1× 47 1.8× 18 399
Dean Wyatte 249 1.0× 81 1.1× 19 0.6× 56 1.9× 31 1.2× 14 370
Luca Ambrogioni 261 1.0× 78 1.1× 35 1.1× 41 1.4× 25 1.0× 23 375
Bradley Caron 266 1.0× 47 0.7× 117 3.5× 30 1.0× 22 0.8× 12 385
Dustin Stansbury 347 1.3× 90 1.3× 12 0.4× 30 1.0× 44 1.7× 7 402
Erin Goddard 318 1.2× 35 0.5× 13 0.4× 17 0.6× 32 1.2× 28 354
Chen-Ping Yu 169 0.6× 150 2.1× 16 0.5× 29 1.0× 33 1.3× 16 301
Corbin A. Cunningham 248 1.0× 52 0.7× 27 0.8× 23 0.8× 50 1.9× 18 371
Yi Chen 240 0.9× 29 0.4× 59 1.8× 34 1.1× 46 1.8× 9 344

Countries citing papers authored by Jacob S. Prince

Since Specialization
Citations

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

Fields of papers citing papers by Jacob S. Prince

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob S. Prince. 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 Jacob S. Prince. The network helps show where Jacob S. Prince may publish in the future.

Co-authorship network of co-authors of Jacob S. Prince

This figure shows the co-authorship network connecting the top 25 collaborators of Jacob S. Prince. A scholar is included among the top collaborators of Jacob S. Prince 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 Jacob S. Prince. Jacob S. Prince 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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