U. Kerzel

30.2k total citations
17 papers, 134 citations indexed

About

U. Kerzel is a scholar working on Mechanical Engineering, Metals and Alloys and Nuclear and High Energy Physics. According to data from OpenAlex, U. Kerzel has authored 17 papers receiving a total of 134 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Mechanical Engineering, 4 papers in Metals and Alloys and 4 papers in Nuclear and High Energy Physics. Recurrent topics in U. Kerzel's work include Non-Destructive Testing Techniques (4 papers), Hydrogen embrittlement and corrosion behaviors in metals (4 papers) and Particle physics theoretical and experimental studies (4 papers). U. Kerzel is often cited by papers focused on Non-Destructive Testing Techniques (4 papers), Hydrogen embrittlement and corrosion behaviors in metals (4 papers) and Particle physics theoretical and experimental studies (4 papers). U. Kerzel collaborates with scholars based in Germany, United Kingdom and Pakistan. U. Kerzel's co-authors include M. Feindt, Sandra Korte‐Kerzel, Talal Al‐Samman, Ehsan Karimi, F. Wick, Aurore Savoy-Navarro, L. Ramler, E. Ben-Haim, Benjamin Berkels and P. Roudeau and has published in prestigious journals such as PLoS ONE, Materials & Design and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

In The Last Decade

U. Kerzel

15 papers receiving 131 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
U. Kerzel Germany 5 59 27 26 21 20 17 134
S. T. French United Kingdom 7 33 0.6× 9 0.3× 14 0.5× 13 0.7× 22 115
Kai Hu China 7 78 1.3× 61 2.3× 4 0.2× 48 2.4× 19 145
B. M. Baughman United States 4 121 2.1× 19 0.7× 37 1.4× 1 0.0× 9 0.5× 11 203
Y. Zheng China 5 25 0.4× 10 0.4× 2 0.1× 7 0.3× 11 64
J. W. Zhao China 6 41 0.7× 22 0.8× 2 0.1× 9 0.5× 21 109
T. Y. Xing China 4 13 0.2× 33 1.2× 3 0.1× 12 0.6× 12 84
O. Gutsche United States 9 94 1.6× 4 0.1× 21 0.8× 6 0.3× 37 222
P. V. Ivanov Russia 7 49 0.8× 4 0.1× 64 2.5× 13 0.7× 27 135
M.Ya. Khabibullin Russia 8 102 1.7× 8 0.3× 5 0.2× 1 0.0× 65 3.3× 40 181
M. Tada Japan 4 50 0.8× 29 1.1× 5 0.2× 4 0.2× 77 3.9× 7 358

Countries citing papers authored by U. Kerzel

Since Specialization
Citations

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

Fields of papers citing papers by U. Kerzel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of U. Kerzel

This figure shows the co-authorship network connecting the top 25 collaborators of U. Kerzel. A scholar is included among the top collaborators of U. Kerzel 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 U. Kerzel. U. Kerzel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Schumacher, Peter, et al.. (2025). Resolution enhancement of scanning electron micrographs using artificial intelligence. Materials & Design. 253. 113955–113955. 1 indexed citations
2.
Xie, Zhuocheng, et al.. (2025). Predicting grain boundary segregation in magnesium alloys: An atomistically informed machine learning approach. Journal of Magnesium and Alloys. 13(6). 2636–2650. 2 indexed citations
3.
Karimi, Ehsan, et al.. (2024). Automated segmentation of large image datasets using artificial intelligence for microstructure characterisation and damage analysis. Materials & Design. 243. 113031–113031. 4 indexed citations
4.
Kerzel, U., et al.. (2023). On the damage behaviour in dual-phase DP800 steel deformed in single and combined strain paths. Materials & Design. 231. 112016–112016. 2 indexed citations
5.
6.
Karimi, Ehsan, et al.. (2023). Three-dimensional characterisation of deformation-induced damage in dual phase steel using deep learning. Materials & Design. 232. 112108–112108. 6 indexed citations
7.
Wick, F., et al.. (2021). Demand Forecasting of Individual Probability Density Functions with Machine Learning. Operations Research Forum. 2(3). 3 indexed citations
8.
9.
Al‐Samman, Talal, et al.. (2019). Large-area, high-resolution characterisation and classification of damage mechanisms in dual-phase steel using deep learning. PLoS ONE. 14(5). e0216493–e0216493. 46 indexed citations
10.
Wick, F., et al.. (2019). Cyclic Boosting - An Explainable Supervised Machine Learning Algorithm. arXiv (Cornell University). 358–363. 4 indexed citations
11.
Kerzel, U.. (2008). The LHCb RICH detectors. Journal of Physics Conference Series. 110(9). 92014–92014.
12.
Kerzel, U.. (2006). The X(3872) at the Tevatron. Nuclear Physics B - Proceedings Supplements. 156(1). 248–251. 1 indexed citations
13.
Feindt, M., et al.. (2005). Fast integration using quasi-random numbers. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 559(1). 232–236. 2 indexed citations
14.
Feindt, M. & U. Kerzel. (2005). The NeuroBayes neural network package. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 559(1). 190–194. 41 indexed citations
15.
Bartsch, V., S. Belforte, R. Illingworth, et al.. (2005). Testing the CDF Distributed Computing Framework. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations
16.
Albrecht, Z., M. Moch, M. Feindt, et al.. (2003). A study of excited $b-$hadron states with the DELPHI detector at LEP. CERN Document Server (European Organization for Nuclear Research).
17.
Barker, Gareth J., U. Kerzel, E. Ben-Haim, et al.. (2002). A Study of the b-Quark Fragmentation Function with the DELPHI Detector at LEP I. CERN Document Server (European Organization for Nuclear Research). 5 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

Breakdown of academic impact, for papers by S. T. French Breakdown of academic impact, for papers by Kai Hu Breakdown of academic impact, for papers by B. M. Baughman Breakdown of academic impact, for papers by Y. Zheng Breakdown of academic impact, for papers by J. W. Zhao Breakdown of academic impact, for papers by T. Y. Xing Breakdown of academic impact, for papers by O. Gutsche Breakdown of academic impact, for papers by P. V. Ivanov Breakdown of academic impact, for papers by M.Ya. Khabibullin Breakdown of academic impact, for papers by M. Tada
Rankless by CCL
2026