Stephan Huckemann

1.3k total citations
41 papers, 589 citations indexed

About

Stephan Huckemann is a scholar working on Geometry and Topology, Applied Mathematics and Signal Processing. According to data from OpenAlex, Stephan Huckemann has authored 41 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Geometry and Topology, 7 papers in Applied Mathematics and 6 papers in Signal Processing. Recurrent topics in Stephan Huckemann's work include Morphological variations and asymmetry (24 papers), Statistical and numerical algorithms (6 papers) and Biometric Identification and Security (6 papers). Stephan Huckemann is often cited by papers focused on Morphological variations and asymmetry (24 papers), Statistical and numerical algorithms (6 papers) and Biometric Identification and Security (6 papers). Stephan Huckemann collaborates with scholars based in Germany, United States and United Kingdom. Stephan Huckemann's 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 and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Stephan Huckemann

38 papers receiving 561 citations

Peers

Stephan Huckemann

CVPR

Huiling Le United Kingdom

Alexey Koloydenko United Kingdom

Vic Patrangenaru United States

D. Barden United Kingdom

T. K. Carne United Kingdom

Sung Nok Chiu Hong Kong

Abraham Boyarsky Canada

Daniel Štefankovič United States

F. Papangelou United Kingdom

Hugo Steinhaus Poland

Huiling Le United Kingdom

Stephan Huckemann

375 ×1.6

160 ×0.9

CVPR

20 ×0.2

91 ×0.8

53 ×0.8

Citations per year, relative to Stephan Huckemann Stephan Huckemann (= 1×) peers Huiling Le

Countries citing papers authored by Stephan Huckemann

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Huckemann, Stephan, et al.. (2024). Finite sample smeariness of Fréchet means with application to climate. Electronic Journal of Statistics. 18(2). 1 indexed citations

Huckemann, Stephan, et al.. (2023). Diffusion means in geometric spaces. Bernoulli. 29(4). 1 indexed citations

Hiller, M., et al.. (2023). Bayesian optimization to estimate hyperfine couplings from 19F ENDOR spectra. Journal of Magnetic Resonance. 353. 107491–107491. 9 indexed citations

Pierrynowski, M.R., et al.. (2023). Confidence tubes for curves on SO(3) and identification of subject-specific gait change after kneeling. Journal of the Royal Statistical Society Series C (Applied Statistics). 72(5). 1354–1374. 2 indexed citations

Mardia, Kanti V., et al.. (2021). Principal component analysis and clustering on manifolds. Journal of Multivariate Analysis. 188. 104862–104862. 7 indexed citations

Pierrynowski, M.R., et al.. (2020). Functional inference on rotational curves under sample‐specific group actions and identification of human gait. Scandinavian Journal of Statistics. 48(4). 1256–1276. 1 indexed citations

Düring, Bertram, et al.. (2019). An anisotropic interaction model for simulating fingerprints. Journal of Mathematical Biology. 78(7). 2171–2206. 5 indexed citations

Gottschlich, Carsten, et al.. (2019). Smudge Noise for Quality Estimation of Fingerprints and its Validation. IEEE Transactions on Information Forensics and Security. 14(8). 1963–1974. 6 indexed citations

Huckemann, Stephan, et al.. (2016). Filter Design and Performance Evaluation for Fingerprint Image Segmentation. PLoS ONE. 11(5). e0154160–e0154160. 25 indexed citations

10.

Hartmann, Alexander K., et al.. (2015). Drift Estimation in Sparse Sequential Dynamic Imaging, With Application to Nanoscale Fluorescence Microscopy. Journal of the Royal Statistical Society Series B (Statistical Methodology). 78(3). 563–587. 1 indexed citations

11.

Feragen, Aasa, Stephan Huckemann, J. S. Marron, & Ezra Miller. (2015). Mini-Workshop: Asymptotic Statistics on Stratified Spaces. Oberwolfach Reports. 11(4). 2481–2527.

12.

Wollnik, Carina, et al.. (2015). The Filament Sensor for Near Real-Time Detection of Cytoskeletal Fiber Structures. PLoS ONE. 10(5). e0126346–e0126346. 57 indexed citations

13.

Hotz, Thomas & Stephan Huckemann. (2014). Intrinsic means on the circle: uniqueness, locus and asymptotics. Annals of the Institute of Statistical Mathematics. 67(1). 177–193. 19 indexed citations

14.

Schulz, Jörn, Sungkyu Jung, Stephan Huckemann, et al.. (2014). Analysis of Rotational Deformations From Directional Data. Journal of Computational and Graphical Statistics. 24(2). 539–560. 9 indexed citations

15.

Bullitt, Elizabeth, Stephan Huckemann, Ezra Miller, et al.. (2014). Tree-Oriented Analysis of Brain Artery Structure. Journal of Mathematical Imaging and Vision. 50(1-2). 126–143. 8 indexed citations

16.

Huckemann, Stephan, Thomas Hotz, & Axel Munk. (2010). Intrinsic shape analysis: Geodesic principal component analysis for Riemannian manifolds modulo Lie group actions. Discussion paper with rejoinder.. Statistica Sinica. 20. 1–100. 49 indexed citations

17.

Huckemann, Stephan, Peter T. Kim, Ja‐Yong Koo, & Axel Munk. (2010). Möbius deconvolution on the hyperbolic plane with application to impedance density estimation. The Annals of Statistics. 38(4). 19 indexed citations

18.

Huckemann, Stephan, Thomas Hotz, & Axel Munk. (2008). Global Models for the Orientation Field of Fingerprints: An Approach Based on Quadratic Differentials. IEEE Transactions on Pattern Analysis and Machine Intelligence. 30(9). 1507–1519. 52 indexed citations

19.

Huckemann, Stephan & Thomas Hotz. (2008). Principal component geodesics for planar shape spaces. Journal of Multivariate Analysis. 100(4). 699–714. 10 indexed citations

20.

Huckemann, Stephan, et al.. (2007). INTRINSIC SHAPE ANALYSIS: GEODESIC PCA FOR RIEMANNIAN MANIFOLDS MODULO ISOMETRIC LIE GROUP ACTIONS. GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen). 80 indexed citations

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.

Explore authors with similar magnitude of impact