Sebastian Kurtek
- Geometry and Topology top 2%
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 5%
- Artificial Intelligence top 10%
- Plant Science
- Co-authors
- Anuj SrivastavaEric KlassenZhaohua DingHamid LagaStanley J. MiklavcicMalcolm J. AvisonYing SunWei Wu
- Topics
- Morphological variations and asymmetry (44 papers)Image Processing and 3D Reconstruction (14 papers)Image Retrieval and Classification Techniques (13 papers)
- Journals
- Journal of the American Statistical AssociationIEEE Transactions on Pattern Analysis and Machine IntelligenceBiometrika
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Sebastian Kurtek
58 papers receiving 748 citations
Peers
Comparison fields: 5 of 103
- Geometry and Topology 370
- Computer Vision and Pattern Recognition 326
- Computational Mechanics 166
- Artificial Intelligence 97
- Plant Science 95
Countries citing papers authored by Sebastian Kurtek
This map shows the geographic impact of Sebastian Kurtek'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 Sebastian Kurtek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Kurtek more than expected).
Fields of papers citing papers by Sebastian Kurtek
This network shows the impact of papers produced by Sebastian Kurtek. 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 Sebastian Kurtek. The network helps show where Sebastian Kurtek may publish in the future.
Co-authorship network of co-authors of Sebastian Kurtek
This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Kurtek. A scholar is included among the top collaborators of Sebastian Kurtek 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 Sebastian Kurtek. Sebastian Kurtek 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 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 7 | |
| 9 | 2 | |
| 10 | 8 | |
| 11 | 27 | |
| 12 | 12 | |
| 13 | 10 | |
| 14 | 43 | |
| 15 | Statistical Analysis and Modeling of Elastic Functions | 13 |
| 16 | Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment | 24 |
| 17 | 52 | |
| 18 | 24 | |
| 19 | 45 | |
| 20 | 39 |
About Sebastian Kurtek
Sebastian Kurtek is a scholar working on Geometry and Topology, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 64 papers that have together received 767 indexed citations. Recurring topics across this work include Morphological variations and asymmetry (44 papers), Image Processing and 3D Reconstruction (14 papers) and Image Retrieval and Classification Techniques (13 papers). The work is most often cited by research in Geometry and Topology (370 citations), Computer Vision and Pattern Recognition (326 citations) and Statistics and Probability (70 citations). Sebastian Kurtek has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Anuj Srivastava, Eric Klassen, Zhaohua Ding, Hamid Laga, Stanley J. Miklavcic, Malcolm J. Avison, Ying Sun, Wei Wu, John C. Gore and Mahmood Reza Golzarian. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and Biometrika.
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.