Matthew McNaughton
- Computer Vision and Pattern Recognition top 5%
- Automotive Engineering top 5%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Sociology and Political Science
- Co-authors
- Chris UrmsonJohn M. DolanJin Woo LeeDuane SzafronJonathan SchaefferMaria CutumisuDavid ParkerMichael Carbonaro
- Topics
- Artificial Intelligence in Games (7 papers)Model-Driven Software Engineering Techniques (6 papers)Software Engineering and Design Patterns (5 papers)
- Partner nations
- CanadaUnited StatesAustralia
In The Last Decade
Matthew McNaughton
20 papers receiving 445 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 246
- Automotive Engineering 244
- Artificial Intelligence 130
- Control and Systems Engineering 128
- Sociology and Political Science 74
Countries citing papers authored by Matthew McNaughton
This map shows the geographic impact of Matthew McNaughton'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 Matthew McNaughton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew McNaughton more than expected).
Fields of papers citing papers by Matthew McNaughton
This network shows the impact of papers produced by Matthew McNaughton. 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 Matthew McNaughton. The network helps show where Matthew McNaughton may publish in the future.
Co-authorship network of co-authors of Matthew McNaughton
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew McNaughton. A scholar is included among the top collaborators of Matthew McNaughton 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 Matthew McNaughton. Matthew McNaughton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 249 | |
| 3 | 39 | |
| 4 | 2 | |
| 5 | 11 | |
| 6 | 29 | |
| 7 | 4 | |
| 8 | 16 | |
| 9 | 8 | |
| 10 | A PATTERN CATALOG FOR COMPUTER ROLE PLAYING GAMES | 15 |
| 11 | 12 | |
| 12 | 2 | |
| 13 | 35 | |
| 14 | Code Generation for AI Scripting in Computer Role-Playing Games | 9 |
| 15 | 7 | |
| 16 | 15 | |
| 17 | 5 | |
| 18 | 15 | |
| 19 | 1 | |
| 20 | 1 |
About Matthew McNaughton
Matthew McNaughton is a scholar working on Software, Development and Archeology, having authored 20 papers that have together received 476 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (7 papers), Model-Driven Software Engineering Techniques (6 papers) and Software Engineering and Design Patterns (5 papers). The work is most often cited by research in Automotive Engineering (244 citations), Computer Vision and Pattern Recognition (246 citations) and Software (36 citations). Matthew McNaughton has collaborated with scholars based in Canada, United States and Australia. Frequent co-authors include Chris Urmson, John M. Dolan, Jin Woo Lee, Duane Szafron, Jonathan Schaeffer, Maria Cutumisu, David Parker, Michael Carbonaro, Hong Zhang and Kevin Waugh. Their work appears in journals such as ISA Transactions, IEEE Intelligent Systems and Science of Computer Programming.
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.