Peter W. McOwan
- Computer Vision and Pattern Recognition top 0.5%
- Experimental and Cognitive Psychology top 0.5%
- Cognitive Neuroscience top 2%
- Social Psychology top 2%
- Artificial Intelligence top 2%
- Co-authors
- Caifeng ShanShaogang GongAlan JohnstonKeith AndersonPaul CurzonGinevra CastellanoIolanda LeiteAna Paiva
- Topics
- Emotion and Mood Recognition (20 papers)Social Robot Interaction and HRI (16 papers)Visual perception and processing mechanisms (16 papers)
- Cited by
- Experimental and Cognitive PsychologyComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Partner nations
- United KingdomPortugalUnited States
In The Last Decade
Peter W. McOwan
88 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Computer Vision and Pattern Recognition 2.3k
- Experimental and Cognitive Psychology 1.8k
- Cognitive Neuroscience 668
- Social Psychology 601
- Artificial Intelligence 527
Countries citing papers authored by Peter W. McOwan
This map shows the geographic impact of Peter W. McOwan'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 Peter W. McOwan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter W. McOwan more than expected).
Fields of papers citing papers by Peter W. McOwan
This network shows the impact of papers produced by Peter W. McOwan. 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 Peter W. McOwan. The network helps show where Peter W. McOwan may publish in the future.
Co-authorship network of co-authors of Peter W. McOwan
This figure shows the co-authorship network connecting the top 25 collaborators of Peter W. McOwan. A scholar is included among the top collaborators of Peter W. McOwan 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 Peter W. McOwan. Peter W. McOwan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 16 | |
| 3 | 6 | |
| 4 | Teaching Formal Methods Using Magic Tricks | 6 |
| 5 | 6 | |
| 6 | 8 | |
| 7 | 8 | |
| 8 | 61 | |
| 9 | 14 | |
| 10 | 12 | |
| 11 | 19 | |
| 12 | 78 | |
| 13 | 225 | |
| 14 | 11 | |
| 15 | 13 | |
| 16 | 13 | |
| 17 | 12 | |
| 18 | 21 | |
| 19 | 9 | |
| 20 | 132 |
About Peter W. McOwan
Peter W. McOwan is a scholar working on Computer Science Applications, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 92 papers that have together received 3.9k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (20 papers), Social Robot Interaction and HRI (16 papers) and Visual perception and processing mechanisms (16 papers). The work is most often cited by research in Experimental and Cognitive Psychology (1.8k citations), Computer Vision and Pattern Recognition (2.3k citations) and Human-Computer Interaction (301 citations). Peter W. McOwan has collaborated with scholars based in United Kingdom, Portugal and United States. Frequent co-authors include Caifeng Shan, Shaogang Gong, Alan Johnston, Keith Anderson, Paul Curzon, Ginevra Castellano, Iolanda Leite, Ana Paiva, André Pereira and Christopher P. Benton. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Current Biology.
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.