Stef van den Elzen
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 5%
- Signal Processing top 5%
- Computational Theory and Mathematics
- Co-authors
- Jarke J. van WijkDanny HoltenJorik BlaasAnna VilanovaNicola PezzottiMichel VerleysenSebastiaan OvereemRafael M. Martins
- Topics
- Data Visualization and Analytics (14 papers)Explainable Artificial Intelligence (XAI) (4 papers)Time Series Analysis and Forecasting (4 papers)
- Partner nations
- NetherlandsGermanyBelgium
In The Last Decade
Stef van den Elzen
14 papers receiving 532 citations
Peers
Comparison fields: 5 of 74
- Computer Vision and Pattern Recognition 441
- Artificial Intelligence 209
- Statistical and Nonlinear Physics 156
- Signal Processing 113
- Computational Theory and Mathematics 35
Countries citing papers authored by Stef van den Elzen
This map shows the geographic impact of Stef van den Elzen'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 Stef van den Elzen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stef van den Elzen more than expected).
Fields of papers citing papers by Stef van den Elzen
This network shows the impact of papers produced by Stef van den Elzen. 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 Stef van den Elzen. The network helps show where Stef van den Elzen may publish in the future.
Co-authorship network of co-authors of Stef van den Elzen
This figure shows the co-authorship network connecting the top 25 collaborators of Stef van den Elzen. A scholar is included among the top collaborators of Stef van den Elzen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stef van den Elzen. Stef van den Elzen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 14 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 10 | |
| 10 | 5 | |
| 11 | 114 | |
| 12 | 93 | |
| 13 | 65 | |
| 14 | 29 | |
| 15 | 78 | |
| 16 | 123 |
About Stef van den Elzen
Stef van den Elzen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence, having authored 16 papers that have together received 550 indexed citations. Recurring topics across this work include Data Visualization and Analytics (14 papers), Explainable Artificial Intelligence (XAI) (4 papers) and Time Series Analysis and Forecasting (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (441 citations), Statistical and Nonlinear Physics (156 citations) and Signal Processing (113 citations). Stef van den Elzen has collaborated with scholars based in Netherlands, Germany and Belgium. Frequent co-authors include Jarke J. van Wijk, Danny Holten, Jorik Blaas, Anna Vilanova, Nicola Pezzotti, Michel Verleysen, Sebastiaan Overeem, Rafael M. Martins, Brian Fisher and Alexandru Telea. Their work appears in journals such as SLEEP, IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum.
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.