Daniel Archambault

85 papers receiving 1.8k citations

Peers

Daniel Archambault
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 1.5k
  • Computer Graphics and Computer-Aided Design 54
  • Statistical and Nonlinear Physics 84
  • Computer Science Applications 33
  • Human-Computer Interaction 31
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Danny Holten Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Archambault

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Archambault

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010211
2 2016124
3 2008120
4 2014119
5 2007116
6 200994
7 201871
8 201352
9 201549
10 201646
11 201544
12 201143
13 201342
14
Structural differences between two graphs through hierarchies
200939
15 201734
16 201233
17 201431
18 201130
19 200729
20 202029

About Daniel Archambault

Daniel Archambault is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications, Computer Graphics and Computer-Aided Design, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 93 papers that have together received 1.9k indexed citations. Recurring topics across this work include Data Visualization and Analytics (69 papers), Complex Network Analysis Techniques (6 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Computational Geometry and Mesh Generation (3 papers), Graph Theory and Algorithms (3 papers), Computer Graphics and Visualization Techniques (2 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Customer churn and segmentation (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Computer Graphics and Computer-Aided Design (54 citations), Statistical and Nonlinear Physics (84 citations), Computer Science Applications (33 citations) and Human-Computer Interaction (31 citations). Daniel Archambault has collaborated with scholars based in United Kingdom, France and Austria. Frequent co-authors include Helen C. Purchase, David Auber, Tamara Munzner, Bruno Pinaud, Paolo Simonetto, Benjamin Bach, Pierre Dragicevic, Christophe Hurter, Sheelagh Carpendale and Huamin Qu. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Lecture notes in computer science, Information Visualization and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.

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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