Thomas Gibson−Robinson

404 total citations
15 papers, 65 citations indexed

About

Thomas Gibson−Robinson is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Thomas Gibson−Robinson has authored 15 papers receiving a total of 65 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 10 papers in Computational Theory and Mathematics and 3 papers in Computer Networks and Communications. Recurrent topics in Thomas Gibson−Robinson's work include Formal Methods in Verification (9 papers), Logic, programming, and type systems (5 papers) and Model-Driven Software Engineering Techniques (2 papers). Thomas Gibson−Robinson is often cited by papers focused on Formal Methods in Verification (9 papers), Logic, programming, and type systems (5 papers) and Model-Driven Software Engineering Techniques (2 papers). Thomas Gibson−Robinson collaborates with scholars based in United Kingdom and United States. Thomas Gibson−Robinson's co-authors include A. W. Roscoe, Michael Goldsmith, Jason R. C. Nurse, Sadie Creese, Duncan Hodges, Jean Scholtz, Gavin Lowe and Arnau Erola and has published in prestigious journals such as Lecture notes in computer science, ACM Transactions on Software Engineering and Methodology and Journal of Computer Security.

In The Last Decade

Thomas Gibson−Robinson

15 papers receiving 61 citations

Peers

Thomas Gibson−Robinson
Comparison fields: 5 of 26
  • Artificial Intelligence 33
  • Computational Theory and Mathematics 26
  • Information Systems 19
  • Computer Networks and Communications 14
  • Software 14
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Citations per field, relative to Thomas Gibson−Robinson
Thomas Gibson−Robinson · 1×
Citations per year, relative to Thomas Gibson−Robinson
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Countries citing papers authored by Thomas Gibson−Robinson

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Gibson−Robinson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Gibson−Robinson. 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 Thomas Gibson−Robinson. The network helps show where Thomas Gibson−Robinson may publish in the future.

Co-authorship network of co-authors of Thomas Gibson−Robinson

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

All Works

15 of 15 papers shown
# Work Indexed citations
1 2
2 2
3 1
4 4
5 1
6 3
7
Computing maximal weak and other bisimulations
1
8 19
9 1
10
FDR into The Cloud
3
11 6
12
The Meaning and Implementation of SKIP in CSP
1
13
Efficient Simulation of CSP−Like Languages
2
14 15
15
Tyger: A Tool for Automatically Simulating CSP−Like Languages in CSP
4

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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