Casey Reas
- Computer Vision and Pattern Recognition top 5%
- Human-Computer Interaction top 5%
- Computer Science Applications top 5%
- Cognitive Neuroscience
- Mechanical Engineering
- Topics
- Art, Technology, and Culture (3 papers)Digital Games and Media (2 papers)Teaching and Learning Programming (2 papers)
- Journals
- AI & SocietyThe MIT Press eBooksCERN Document Server (European Organization for Nuclear Research)
- Partner nations
- United StatesNew Zealand
In The Last Decade
Casey Reas
17 papers receiving 449 citations
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 149
- Human-Computer Interaction 112
- Computer Science Applications 98
- Cognitive Neuroscience 68
- Mechanical Engineering 54
Countries citing papers authored by Casey Reas
This map shows the geographic impact of Casey Reas'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 Casey Reas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Casey Reas more than expected).
Fields of papers citing papers by Casey Reas
This network shows the impact of papers produced by Casey Reas. 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 Casey Reas. The network helps show where Casey Reas may publish in the future.
Co-authorship network of co-authors of Casey Reas
This figure shows the co-authorship network connecting the top 25 collaborators of Casey Reas. A scholar is included among the top collaborators of Casey Reas 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 Casey Reas. Casey Reas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Getting started with Processing.py : making interactive graphics with Python's Processing mode | 1 |
| 2 | 3 | |
| 3 | Getting Started with Processing: A Hands-On Introduction to Making Interactive Graphics | 6 |
| 4 | 3 | |
| 5 | Form+Code in Design, Art, and Architecture | 28 |
| 6 | Getting Started with Processing | 22 |
| 7 | 3 | |
| 8 | Processing a programming handbook for visual designers and artists | 276 |
| 9 | 102 | |
| 10 | 3 | |
| 11 | 9 | |
| 12 | 9 | |
| 13 | 6 | |
| 14 | 4 | |
| 15 | 33 | |
| 16 | 1 | |
| 17 | 1 |
About Casey Reas
Casey Reas is a scholar working on Visual Arts and Performing Arts, Architecture and Human Factors and Ergonomics, having authored 17 papers that have together received 510 indexed citations. Recurring topics across this work include Art, Technology, and Culture (3 papers), Digital Games and Media (2 papers) and Teaching and Learning Programming (2 papers). The work is most often cited by research in Architecture (45 citations), Human-Computer Interaction (112 citations) and Computer Science Applications (98 citations). Casey Reas has collaborated with scholars based in United States and New Zealand. Frequent co-authors include Ben Fry, John Maeda, Benjamin Fry, Lee Martin, Mark Marino, Ian Bogost, Nick Montfort, Michael Mateas, Colin Dixon and John B. Bell. Their work appears in journals such as AI & Society, The MIT Press eBooks and CERN Document Server (European Organization for Nuclear Research).
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.