Mike Paterson

166 total papers · 7.1k total citations
102 papers, 4.2k citations indexed

About

Mike Paterson is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Mike Paterson has authored 102 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 37 papers in Computational Theory and Mathematics and 14 papers in Computer Networks and Communications. Recurrent topics in Mike Paterson's work include Complexity and Algorithms in Graphs (14 papers), Algorithms and Data Compression (12 papers) and semigroups and automata theory (11 papers). Mike Paterson is often cited by papers focused on Complexity and Algorithms in Graphs (14 papers), Algorithms and Data Compression (12 papers) and semigroups and automata theory (11 papers). Mike Paterson collaborates with scholars based in United Kingdom, United States and Australia. Mike Paterson's co-authors include C. B. Raleigh, J. Ian Munro, Manuela Fischer, Lionel Weiss, Mark N. Wegman, Leslie Ann Goldberg, Fei Yao, Uri Zwick, David Eppstein and D Luckham and has published in prestigious journals such as Nature, Journal of Geophysical Research Atmospheres and Journal of Applied Physics.

In The Last Decade

Mike Paterson

97 papers receiving 3.7k citations

Hit Papers

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Author Peers

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

Author Last Decade Papers Cites
Mike Paterson 1.3k 1.2k 1.1k 689 541 102 4.2k
Andreas Griewank 750 0.6× 203 0.2× 2.3k 2.1× 286 0.4× 320 0.6× 113 6.7k
Jonathan Richard Shewchuk 361 0.3× 320 0.3× 432 0.4× 396 0.6× 273 0.5× 61 5.8k
George E. Forsythe 400 0.3× 126 0.1× 1.4k 1.3× 537 0.8× 310 0.6× 75 6.2k
D. C. Sorensen 520 0.4× 124 0.1× 2.3k 2.1× 321 0.5× 354 0.7× 74 6.9k
Eric Darve 329 0.2× 258 0.2× 489 0.5× 507 0.7× 268 0.5× 130 5.2k
Timothy A. Davis 920 0.7× 225 0.2× 2.7k 2.5× 476 0.7× 1.5k 2.8× 108 8.4k
C. T. Kelley 688 0.5× 105 0.1× 2.2k 2.0× 370 0.5× 274 0.5× 185 7.4k
Walter Murray 554 0.4× 108 0.1× 2.2k 2.1× 336 0.5× 321 0.6× 101 8.4k
Philip E. Gill 560 0.4× 114 0.1× 2.4k 2.3× 383 0.6× 326 0.6× 86 9.1k
H. C. Watson 1.3k 1.0× 797 0.7× 572 0.5× 73 0.1× 193 0.4× 93 4.0k

Countries citing papers authored by Mike Paterson

Since Specialization
Citations

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

Fields of papers citing papers by Mike Paterson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mike Paterson

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