Eric D. Ragan

94 papers receiving 2.3k citations

Peers

Eric D. Ragan
Comparison fields: 5 of 128
  • Human-Computer Interaction 1.2k
  • Computer Vision and Pattern Recognition 846
  • Health Informatics 50
  • Radiological and Ultrasound Technology 110
  • Cognitive Neuroscience 423
Replace Aaron Steinfeld with:
Aaron Steinfeld United States
Jean Scholtz United States
Andreas Butz Germany
Dan R. Olsen United States
Eduardo Velloso Australia
Andreas Riener Germany
Maya Çakmak United States
Jaziar Radianti Norway
Thomas Kosch Germany
Maximino Bessa Portugal
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Citations per field
00.5×1.6×
Aaron Steinfeld · 1×
Citations per year

Countries citing papers authored by Eric D. Ragan

Since Specialization
Citations

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

Fields of papers citing papers by Eric D. Ragan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric D. Ragan. 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 Eric D. Ragan. The network helps show where Eric D. Ragan may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric D. Ragan, 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 Eric D. Ragan Line = papers co-authored together Eric D. Ragan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 101 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015187
2 2015162
3 2019160
4 2012141
5 2018118
6 2010116
7 2014107
8 201299
9 202170
10 201662
11 201862
12 201961
13 200960
14 201845
15 201243
16
A Survey of Evaluation Methods and Measures for Interpretable Machine Learning
201842
17 201742
18 202039
19 202037
20 201137

About Eric D. Ragan

Eric D. Ragan is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence and Automotive Engineering, having authored 101 papers that have together received 2.4k indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (40 papers), Spatial Cognition and Navigation (18 papers), Data Visualization and Analytics (17 papers), Augmented Reality Applications (17 papers), Tactile and Sensory Interactions (12 papers), Explainable Artificial Intelligence (XAI) (11 papers), Visual and Cognitive Learning Processes (8 papers) and Human-Automation Interaction and Safety (7 papers). The work is most often cited by research in Human-Computer Interaction (1.2k citations), Computer Vision and Pattern Recognition (846 citations), Health Informatics (50 citations), Radiological and Ultrasound Technology (110 citations) and Cognitive Neuroscience (423 citations). Eric D. Ragan has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Doug A. Bowman, Ryan P. McMahan, Régis Kopper, Yangming Shi, Jing Du, Siroberto Scerbo, Alex Endert, Mohamed Suhail, Jibonananda Sanyal and Sina Mohseni. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, ACM Transactions on Interactive Intelligent Systems, IEEE Computer Graphics and Applications, Communications of the ACM and Journal of the American Medical Informatics Association.

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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