Stephan Huckemann
- Geometry and Topology top 2%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Co-authors
- Axel MunkThomas HotzCarsten GottschlichHerbert ZiezoldCarina WollnikFlorian RehfeldtKanti V. MardiaJa‐Yong Koo
- Topics
- Morphological variations and asymmetry (24 papers)Statistical and numerical algorithms (6 papers)Biometric Identification and Security (6 papers)
- Journals
- Proceedings of the National Academy of SciencesPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Stephan Huckemann
38 papers receiving 561 citations
Peers
Comparison fields: 5 of 97
- Geometry and Topology 236
- Computer Vision and Pattern Recognition 180
- Signal Processing 111
- Artificial Intelligence 108
- Statistics and Probability 63
Countries citing papers authored by Stephan Huckemann
This map shows the geographic impact of Stephan Huckemann'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 Stephan Huckemann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephan Huckemann more than expected).
Fields of papers citing papers by Stephan Huckemann
This network shows the impact of papers produced by Stephan Huckemann. 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 Stephan Huckemann. The network helps show where Stephan Huckemann may publish in the future.
Co-authorship network of co-authors of Stephan Huckemann
This figure shows the co-authorship network connecting the top 25 collaborators of Stephan Huckemann. A scholar is included among the top collaborators of Stephan Huckemann 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 Stephan Huckemann. Stephan Huckemann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 6 | |
| 9 | 25 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 57 | |
| 13 | 19 | |
| 14 | 9 | |
| 15 | 8 | |
| 16 | Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions. Discussion paper with rejoinder. | 49 |
| 17 | 19 | |
| 18 | 52 | |
| 19 | 10 | |
| 20 | INTRINSIC SHAPE ANALYSIS: GEODESIC PCA FOR RIEMANNIAN MANIFOLDS MODULO ISOMETRIC LIE GROUP ACTIONS | 80 |
About Stephan Huckemann
Stephan Huckemann is a scholar working on Geometry and Topology, Biophysics and Applied Mathematics, having authored 41 papers that have together received 589 indexed citations. Recurring topics across this work include Morphological variations and asymmetry (24 papers), Statistical and numerical algorithms (6 papers) and Biometric Identification and Security (6 papers). The work is most often cited by research in Geometry and Topology (236 citations), Signal Processing (111 citations) and Computer Vision and Pattern Recognition (180 citations). Stephan Huckemann has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Axel Munk, Thomas Hotz, Carsten Gottschlich, Herbert Ziezold, Carina Wollnik, Florian Rehfeldt, Kanti V. Mardia, Ja‐Yong Koo, Peter T. Kim and M.R. Pierrynowski. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.