Stuart J. Inglis
Impact in
- Software top 10%
- Software Testing and Debugging Techniques
- Software Reliability and Analysis Research
- Artificial Intelligence top 10%
- Algorithms and Data Compression
- Machine Learning and Data Classification
- Neural Networks and Applications
Papers in
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- Advanced Data Compression Techniques 3
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- Algorithms and Data Compression 3
- Co-authors
- Ian H. Witten (5 shared papers)Geoffrey Holmes (1 shared paper)Eibe Frank (1 shared paper)Yong Wang (1 shared paper)Sean A. Irvine (2 shared papers)John G. Cleary (2 shared papers)Leonard E. Trigg (1 shared paper)Mark Utting (1 shared paper)
- Journals
- Computer (1 paper)Proceedings of the IEEE (1 paper)Journal of Computational Biology (1 paper)Machine Learning (1 paper)Physics Today (1 paper)
- Partner nations
- New ZealandUnited KingdomUnited States
In The Last Decade
Stuart J. Inglis
13 papers receiving 438 citations
Peers
Comparison fields: 5 of 119
- Software 50
- Artificial Intelligence 166
- Computer Vision and Pattern Recognition 90
- Information Systems 96
- Signal Processing 44
Countries citing papers authored by Stuart J. Inglis
This map shows the geographic impact of Stuart J. Inglis'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 Stuart J. Inglis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stuart J. Inglis more than expected).
Fields of papers citing papers by Stuart J. Inglis
This network shows the impact of papers produced by Stuart J. Inglis. 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 Stuart J. Inglis. The network helps show where Stuart J. Inglis may publish in the future.
Co-authors
The 19 scholars most cited alongside Stuart J. Inglis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 266 | |
| 2 | 2014 | 52 | |
| 3 | 2007 | 48 | |
| 4 | 1994 | 35 | |
| 5 | 2002 | 22 | |
| 6 | 2012 | 22 | |
| 7 | 1994 | 14 | |
| 8 | 1961 | 2 | |
| 9 | 1971 | 2 | |
| 10 | 1956 | 1 | |
| 11 | 2002 | 1 | |
| 12 | 2002 | 1 | |
| 13 | 1962 | 1 | |
| 14 | Passenger rolling stock – blast, fire, passenger flow and intercar doors | 2014 | 0 |
About Stuart J. Inglis
Stuart J. Inglis is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Theory and Mathematics, Civil and Structural Engineering and Signal Processing, having authored 14 papers that have together received 467 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (3 papers), Algorithms and Data Compression (3 papers), Transportation Safety and Impact Analysis (1 paper), Structural Response to Dynamic Loads (1 paper), Stellar, planetary, and galactic studies (1 paper), Software Testing and Debugging Techniques (1 paper), Software Reliability and Analysis Research (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Software (50 citations), Artificial Intelligence (166 citations), Computer Vision and Pattern Recognition (90 citations), Information Systems (96 citations) and Signal Processing (44 citations). Stuart J. Inglis has collaborated with scholars based in New Zealand, United Kingdom and United States. Frequent co-authors include Ian H. Witten, Geoffrey Holmes, Eibe Frank, Yong Wang, Sean A. Irvine, John G. Cleary, Leonard E. Trigg, Mark Utting, Alistair Moffat and Tim Bell. Their work appears in journals such as Computer, Proceedings of the IEEE, Journal of Computational Biology, Machine Learning and Physics Today.
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.