Joe Mattis
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Sociology and Political Science top 10%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Steven F. RothJohn KolojejchickJade GoldsteinMei C. ChuahJohanna D. MooreGiuseppe CareniniVibhu O. MittalP. Sheng
- Topics
- Data Visualization and Analytics (12 papers)Multimedia Communication and Technology (7 papers)Video Analysis and Summarization (5 papers)
- Journals
- International Journal of Human-Computer StudiesJournal of Visual Languages & ComputingEdinburgh Research Explorer (University of Edinburgh)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Joe Mattis
15 papers receiving 460 citations
Peers
Comparison fields: 5 of 55
- Computer Vision and Pattern Recognition 428
- Artificial Intelligence 191
- Sociology and Political Science 127
- Signal Processing 103
- Computer Networks and Communications 92
Countries citing papers authored by Joe Mattis
This map shows the geographic impact of Joe Mattis'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 Joe Mattis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joe Mattis more than expected).
Fields of papers citing papers by Joe Mattis
This network shows the impact of papers produced by Joe Mattis. 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 Joe Mattis. The network helps show where Joe Mattis may publish in the future.
Co-authorship network of co-authors of Joe Mattis
This figure shows the co-authorship network connecting the top 25 collaborators of Joe Mattis. A scholar is included among the top collaborators of Joe Mattis 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 Joe Mattis. Joe Mattis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 26 | |
| 2 | 7 | |
| 3 | 24 | |
| 4 | 28 | |
| 5 | Functional Unification Approach to Automated Visualization Design | 1 |
| 6 | Generating explanatory captions for information graphics | 37 |
| 7 | 10 | |
| 8 | 13 | |
| 9 | 47 | |
| 10 | 136 | |
| 11 | 30 | |
| 12 | 3 | |
| 13 | 22 | |
| 14 | 142 | |
| 15 | 11 |
About Joe Mattis
Joe Mattis is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Graphics and Computer-Aided Design, having authored 15 papers that have together received 537 indexed citations. Recurring topics across this work include Data Visualization and Analytics (12 papers), Multimedia Communication and Technology (7 papers) and Video Analysis and Summarization (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (428 citations), Signal Processing (103 citations) and Human-Computer Interaction (44 citations). Joe Mattis has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Steven F. Roth, John Kolojejchick, Jade Goldstein, Mei C. Chuah, Johanna D. Moore, Giuseppe Carenini, Vibhu O. Mittal, P. Sheng and Nancy L. Green. Their work appears in journals such as International Journal of Human-Computer Studies, Journal of Visual Languages & Computing and Edinburgh Research Explorer (University of Edinburgh).
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.