Jon McCormack

57 papers receiving 596 citations

Peers

Jon McCormack
Comparison fields: 5 of 111
  • Architecture 37
  • Computer Graphics and Computer-Aided Design 78
  • Human-Computer Interaction 118
  • Computer Vision and Pattern Recognition 297
  • Signal Processing 98
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Juan Romero Spain
Casey Reas United States
Gillian Smith United States
Oliver Bown Australia
Andy Hunt United Kingdom
Rebecca Fiebrink United Kingdom
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Countries citing papers authored by Jon McCormack

Since Specialization
Citations

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

Fields of papers citing papers by Jon McCormack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jon McCormack, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jon McCormack Line = papers co-authored together Jon McCormack links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199856
2
Grammar-based music composition
199650
3 202040
4 201236
5 201934
6 200934
7
Art, emergence, and the computational sublime
200132
8
Interactive evolution of L-System grammars for computer graphics modelling
199330
9 201329
10 201225
11 202025
12 202120
13 200720
14 201816
15 200316
16 201916
17
Heroic versus collaborative AI for the arts
201515
18 200312
19
Leonardo: Journal of the International Society for the Arts, Sciences and Technology
200112
20 201911

About Jon McCormack

Jon McCormack is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Mechanical Engineering, Human-Computer Interaction and Artificial Intelligence, having authored 63 papers that have together received 683 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (21 papers), Creativity in Education and Neuroscience (9 papers), Aesthetic Perception and Analysis (9 papers), Design Education and Practice (8 papers), Music and Audio Processing (8 papers), Artificial Intelligence in Games (7 papers), Art, Technology, and Culture (7 papers) and Data Visualization and Analytics (7 papers). The work is most often cited by research in Architecture (37 citations), Computer Graphics and Computer-Aided Design (78 citations), Human-Computer Interaction (118 citations), Computer Vision and Pattern Recognition (297 citations) and Signal Processing (98 citations). Jon McCormack has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Alan Dorin, Mark d’Inverno, A. Sherstyuk, Oliver Bown, Taras Kowaliw, Toby Gifford, Matthew Yee-King, Alice Eldridge, Mitchell Whitelaw and Ryan Kelly. Their work appears in journals such as BDJ, Leonardo, Organised Sound, Complexity and IEEE Transactions on Evolutionary Computation.

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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