Michael Correll
Impact in
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- Data Visualization and Analytics
- Human-Computer Interaction top 5%
- Innovative Human-Technology Interaction
- Usability and User Interface Design
Papers in
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- Data Visualization and Analytics 44
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- Viral Infections and Vectors 2
- Co-authors
- Michael Lee Gleicher (15 shared papers)Melanie K. Tory (3 shared papers)Jeffrey Heer (4 shared papers)Lyn Bartram (2 shared papers)Alper Sarıkaya (3 shared papers)Danyel Fisher (1 shared paper)Steven Franconeri (4 shared papers)Danielle Albers (4 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (12 papers)Computer Graphics Forum (4 papers)Journal of Virology (2 papers)Behavior Research Methods (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Michael Correll
50 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 106
- Computer Vision and Pattern Recognition 1.3k
- Human-Computer Interaction 69
- General Decision Sciences 24
- Computer Science Applications 37
- Virology 24
Countries citing papers authored by Michael Correll
This map shows the geographic impact of Michael Correll'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 Michael Correll with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Correll more than expected).
Fields of papers citing papers by Michael Correll
This network shows the impact of papers produced by Michael Correll. 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 Michael Correll. The network helps show where Michael Correll may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Correll, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 256 | |
| 2 | 2014 | 194 | |
| 3 | 2018 | 127 | |
| 4 | 2019 | 122 | |
| 5 | 2013 | 84 | |
| 6 | 2014 | 83 | |
| 7 | 2020 | 72 | |
| 8 | 2018 | 69 | |
| 9 | 2012 | 59 | |
| 10 | 2018 | 51 | |
| 11 | 2017 | 47 | |
| 12 | 2021 | 43 | |
| 13 | 2020 | 42 | |
| 14 | 2016 | 35 | |
| 15 | 2014 | 34 | |
| 16 | 2011 | 33 | |
| 17 | 2023 | 29 | |
| 18 | 2019 | 28 | |
| 19 | 2014 | 26 | |
| 20 | 2011 | 25 |
About Michael Correll
Michael Correll is a scholar working on Computer Vision and Pattern Recognition, Infectious Diseases, General Social Sciences, Virology and Geography, Planning and Development, having authored 51 papers that have together received 1.7k indexed citations. Recurring topics across this work include Data Visualization and Analytics (44 papers), Viral Infections and Vectors (2 papers), Data Quality and Management (1 paper), Usability and User Interface Design (1 paper), Time Series Analysis and Forecasting (1 paper), HIV Research and Treatment (1 paper), Big Data and Business Intelligence (1 paper) and Digital Humanities and Scholarship (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Human-Computer Interaction (69 citations), General Decision Sciences (24 citations), Computer Science Applications (37 citations) and Virology (24 citations). Michael Correll has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Michael Lee Gleicher, Melanie K. Tory, Jeffrey Heer, Lyn Bartram, Alper Sarıkaya, Danyel Fisher, Steven Franconeri, Danielle Albers, Gordon Kindlmann and Matthew Kay. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Journal of Virology, Behavior Research Methods and PLoS ONE.
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.