Jon Fairbairn

14 total papers · 1.6k total citations
10 papers, 709 citations indexed

About

Jon Fairbairn is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Jon Fairbairn has authored 10 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 2 papers in Information Systems. Recurrent topics in Jon Fairbairn's work include Logic, programming, and type systems (7 papers), Formal Methods in Verification (3 papers) and Software Engineering Research (2 papers). Jon Fairbairn is often cited by papers focused on Logic, programming, and type systems (7 papers), Formal Methods in Verification (3 papers) and Software Engineering Research (2 papers). Jon Fairbairn collaborates with scholars based in United Kingdom, United States and South Sudan. Jon Fairbairn's co-authors include Kevin Hammond, Paul Hudak, Joseph H. Fasel, Philip Wadler, Thomas Johnsson, Will Partain, John Hughes, Rishiyur S. Nikhil, John Peterson and Simon Peyton Jones and has published in prestigious journals such as ACM SIGPLAN Notices, Software Practice and Experience and Science of Computer Programming.

In The Last Decade

Jon Fairbairn

5 papers receiving 598 citations

Hit Papers

Report on the programming... 1992 2026 2003 2014 1992 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Jon Fairbairn 576 314 222 172 124 10 709
Will Partain 597 1.0× 331 1.1× 239 1.1× 185 1.1× 127 1.0× 6 739
Joseph H. Fasel 638 1.1× 355 1.1× 254 1.1× 203 1.2× 131 1.1× 8 815
Thomas Johnsson 674 1.2× 387 1.2× 308 1.4× 212 1.2× 143 1.2× 8 863
Guillermo J. Rozas 542 0.9× 255 0.8× 283 1.3× 165 1.0× 146 1.2× 11 711
Kent M. Pitman 563 1.0× 254 0.8× 284 1.3× 167 1.0× 156 1.3× 16 740
M. Wand 652 1.1× 323 1.0× 311 1.4× 180 1.0× 167 1.3× 11 828
C. Strachey 539 0.9× 328 1.0× 135 0.6× 170 1.0× 110 0.9× 14 817
D. H. Bartley 548 1.0× 257 0.8× 285 1.3× 161 0.9× 149 1.2× 5 714
E. A. Ashcroft 397 0.7× 319 1.0× 303 1.4× 256 1.5× 65 0.5× 24 758
Liviu Tancau 296 0.5× 218 0.7× 170 0.8× 133 0.8× 226 1.8× 8 622

Countries citing papers authored by Jon Fairbairn

Since Specialization
Citations

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

Fields of papers citing papers by Jon Fairbairn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jon Fairbairn

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