Aurélien Tabard

1.3k citations
58 papers · 951 · h-index 13

Impact in

Papers in

Aurélien Tabard

55 papers receiving 910 citations

Peers

Aurélien Tabard
Comparison fields: 5 of 78
  • Human-Computer Interaction 292
  • Information Systems and Management 167
  • Computer Vision and Pattern Recognition 344
  • Computer Science Applications 69
  • Information Systems 213
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Citations per year

Countries citing papers authored by Aurélien Tabard

Since Specialization
Citations

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

Fields of papers citing papers by Aurélien Tabard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aurélien Tabard. 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 Aurélien Tabard. The network helps show where Aurélien Tabard may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018253
2 201486
3 202185
4 200864
5 202054
6 201851
7 201849
8 201732
9 201625
10 201120
11 201217
12 201915
13 200714
14 201413
15 201712
16 20219
17 20138
18 20188
19
Using and Perceiving Emoji in Design Peer Feedback
20198
20 20208

About Aurélien Tabard

Aurélien Tabard is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Information Systems and Management, Information Systems and Developmental and Educational Psychology, having authored 58 papers that have together received 951 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (17 papers), Data Visualization and Analytics (14 papers), Innovative Human-Technology Interaction (13 papers), Innovative Teaching and Learning Methods (6 papers), Usability and User Interface Design (4 papers), Personal Information Management and User Behavior (4 papers), Education and Technology Integration (3 papers) and Intelligent Tutoring Systems and Adaptive Learning (3 papers). The work is most often cited by research in Human-Computer Interaction (292 citations), Information Systems and Management (167 citations), Computer Vision and Pattern Recognition (344 citations), Computer Science Applications (69 citations) and Information Systems (213 citations). Aurélien Tabard has collaborated with scholars based in France, Denmark and United States. Frequent co-authors include Adam Rule, James D. Hollan, Wendy E. Mackay, Élise Lavoué, Evelyn Eastmond, Andreas Martin Butz, Jakob E. Bardram, Henrik Korsgaard, Juan David Hincapié-Ramos and Rohit Ashok Khot. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Proceedings of the ACM on Human-Computer Interaction, International Journal of Human-Computer Studies, Computer Graphics Forum and ACM Transactions on Computer-Human Interaction.

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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