David R. Flatla

1.0k citations
38 papers · 708 indexed · h-index 16

Impact in

Papers in

David R. Flatla

37 papers receiving 675 citations

Peers

David R. Flatla
Comparison fields: 5 of 85
  • Human-Computer Interaction 290
  • Human Factors and Ergonomics 64
  • Cognitive Neuroscience 271
  • Developmental and Educational Psychology 115
  • Computer Vision and Pattern Recognition 161
Replace Kirsten Ellis with:
Kirsten Ellis Australia
Danielle Bragg United States
Orly Lahav Israel
Oussama Metatla United Kingdom
Raja Kushalnagar United States
Joshua Hailpern United States
Chris Creed United Kingdom
Garreth W. Tigwell United States
Sandra Baldassarri Spain
Pascal Guitton France
David R. Flatla relative to Kirsten Ellis Australia Kirsten Ellis's profile →
Citations per field
00.5×
Kirsten Ellis · 1×
Citations per year

Countries citing papers authored by David R. Flatla

Since Specialization
Citations

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

Fields of papers citing papers by David R. Flatla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David R. Flatla. 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 David R. Flatla. The network helps show where David R. Flatla may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20234
3 20213
4 20192
5 20198
6 201820
7 201826
8 20186
9 201726
10 20179
11 201711
12 201631
13 201687
14 201322
15 201319
16 201231
17 201217
18 20117
19 201118
20 201025

About David R. Flatla

David R. Flatla is a scholar working on Human-Computer Interaction, Cognitive Neuroscience, Human Factors and Ergonomics, Social Psychology and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 708 indexed citations. Recurring topics across this work include Tactile and Sensory Interactions (16 papers), Color Science and Applications (14 papers), Visual perception and processing mechanisms (13 papers), Color perception and design (12 papers), Interactive and Immersive Displays (6 papers), Hearing Impairment and Communication (4 papers), Digital Accessibility for Disabilities (3 papers) and Augmented Reality Applications (3 papers). The work is most often cited by research in Human-Computer Interaction (290 citations), Human Factors and Ergonomics (64 citations), Cognitive Neuroscience (271 citations), Developmental and Educational Psychology (115 citations) and Computer Vision and Pattern Recognition (161 citations). David R. Flatla has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Carl Gutwin, Garreth W. Tigwell, Scott Bateman, Lennart E. Nacke, Regan L. Mandryk, Rachel Menzies, Juan David Hincapié-Ramos, Pourang Irani, Katharina Reinecke and Christopher Brooks. Their work appears in journals such as Behaviour and Information Technology, ACM Transactions on Accessible Computing, ACM SIGACCESS Accessibility and Computing, Graphics Interface and Electronic Imaging.

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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