Lukas Exl

752 total citations
32 papers, 493 citations indexed

About

Lukas Exl is a scholar working on Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering. According to data from OpenAlex, Lukas Exl has authored 32 papers receiving a total of 493 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Atomic and Molecular Physics, and Optics, 16 papers in Electronic, Optical and Magnetic Materials and 8 papers in Electrical and Electronic Engineering. Recurrent topics in Lukas Exl's work include Magnetic Properties and Applications (16 papers), Magnetic properties of thin films (11 papers) and Electromagnetic Simulation and Numerical Methods (7 papers). Lukas Exl is often cited by papers focused on Magnetic Properties and Applications (16 papers), Magnetic properties of thin films (11 papers) and Electromagnetic Simulation and Numerical Methods (7 papers). Lukas Exl collaborates with scholars based in Austria, Japan and Germany. Lukas Exl's co-authors include T. Schrefl, Dieter Suess, Claas Abert, André Drews, Alexander Kovacs, Johann Fischbacher, Norbert J. Mauser, Markus Gusenbauer, Harald Oezelt and Florian Bruckner and has published in prestigious journals such as Journal of Applied Physics, Journal of Computational Physics and Computer Physics Communications.

In The Last Decade

Lukas Exl

31 papers receiving 477 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lukas Exl Austria 12 320 290 105 69 68 32 493
Jongbae Hong South Korea 14 294 0.9× 142 0.5× 102 1.0× 161 2.3× 275 4.0× 40 658
R. Hempstead United States 8 397 1.2× 208 0.7× 115 1.1× 74 1.1× 36 0.5× 16 520
Jianyu Zhang China 12 436 1.4× 189 0.7× 217 2.1× 136 2.0× 9 0.1× 39 598
Yoshihisa Nakamura Japan 12 348 1.1× 187 0.6× 86 0.8× 102 1.5× 19 0.3× 90 447
I.A. Beardsley United States 11 347 1.1× 247 0.9× 76 0.7× 105 1.5× 8 0.1× 20 434
Haijing Zhou China 13 146 0.5× 111 0.4× 381 3.6× 20 0.3× 19 0.3× 86 578
H. Aoi Japan 15 785 2.5× 504 1.7× 128 1.2× 236 3.4× 10 0.1× 85 886
Anders Eklund Sweden 15 878 2.7× 159 0.5× 436 4.2× 410 5.9× 46 0.7× 31 1.1k
Nan-Hsiung Yeh United States 10 213 0.7× 114 0.4× 112 1.1× 93 1.3× 8 0.1× 30 348
Nam Kim South Korea 15 408 1.3× 48 0.2× 227 2.2× 116 1.7× 33 0.5× 47 632

Countries citing papers authored by Lukas Exl

Since Specialization
Citations

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

Fields of papers citing papers by Lukas Exl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Exl

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

All Works

20 of 20 papers shown
1.
Zitz, Jeffrey A., et al.. (2025). Explainable machine learning and feature engineering applied to nanoindentation data. Materials & Design. 253. 113897–113897. 3 indexed citations
2.
Kovacs, Alexander, Lukas Exl, Johann Fischbacher, et al.. (2024). Image-based prediction and optimization of hysteresis properties of nanocrystalline permanent magnets using deep learning. Journal of Magnetism and Magnetic Materials. 596. 171937–171937. 3 indexed citations
3.
Exl, Lukas, et al.. (2022). Bridging Fidelities to Predict Nanoindentation Tip Radii Using Interpretable Deep Learning Models. JOM. 74(6). 2195–2205. 4 indexed citations
4.
Kovacs, Alexander, Lukas Exl, Johann Fischbacher, et al.. (2022). Magnetostatics and micromagnetics with physics informed neural networks. Journal of Magnetism and Magnetic Materials. 548. 168951–168951. 40 indexed citations
5.
Kovacs, Alexander, Lukas Exl, Johann Fischbacher, et al.. (2022). Exploring the Hysteresis Properties of Nanocrystalline Permanent Magnets Using Deep Learning. SSRN Electronic Journal. 1 indexed citations
6.
Mauser, Norbert J., et al.. (2021). Machine Learning Methods for the Prediction of Micromagnetic Magnetization Dynamics. IEEE Transactions on Magnetics. 58(2). 1–6. 5 indexed citations
7.
Exl, Lukas, et al.. (2021). Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method. Journal of Computational Physics. 444. 110586–110586. 5 indexed citations
8.
Exl, Lukas, Norbert J. Mauser, T. Schrefl, & Dieter Suess. (2020). Learning time-stepping by nonlinear dimensionality reduction to predict magnetization dynamics. Communications in Nonlinear Science and Numerical Simulation. 84. 105205–105205. 7 indexed citations
9.
Langen, Tim, et al.. (2019). Optimal control of the self-bound dipolar droplet formation process. Computer Physics Communications. 244. 205–216. 2 indexed citations
10.
Exl, Lukas, et al.. (2019). Computational micromagnetics with Commics. Computer Physics Communications. 248. 106965–106965. 11 indexed citations
11.
Exl, Lukas. (2019). An optimization approach for dynamical Tucker tensor approximation. Results in Applied Mathematics. 1. 100002–100002.
12.
Exl, Lukas. (2018). A magnetostatic energy formula arising from the L2-orthogonal decomposition of the stray field. Journal of Mathematical Analysis and Applications. 467(1). 230–237. 3 indexed citations
13.
Lode, Axel U. J., Paolo Molignini, Rui Lin, et al.. (2018). Many-body physics in two-component Bose–Einstein condensates in a cavity: fragmented superradiance and polarization. New Journal of Physics. 20(5). 55006–55006. 18 indexed citations
14.
Fischbacher, Johann, Alexander Kovacs, Lukas Exl, et al.. (2017). Searching the weakest link: Demagnetizing fields and magnetization reversal in permanent magnets. Scripta Materialia. 154. 253–258. 32 indexed citations
15.
Fischbacher, Johann, Alexander Kovacs, Harald Oezelt, et al.. (2017). Nonlinear conjugate gradient methods in micromagnetics. AIP Advances. 7(4). 39 indexed citations
16.
Exl, Lukas & T. Schrefl. (2014). Non-uniform FFT for the finite element computation of the micromagnetic scalar potential. Journal of Computational Physics. 270. 490–505. 10 indexed citations
17.
Gusenbauer, Markus, Johann Fischbacher, Lukas Exl, et al.. (2013). Simulation of magnetic active polymers for versatile microfluidic devices. Springer Link (Chiba Institute of Technology). 4 indexed citations
18.
Gusenbauer, Markus, Lukas Exl, S. Bance, et al.. (2013). Guided self-assembly of magnetic beads for biomedical applications. Physica B Condensed Matter. 435. 21–24. 4 indexed citations
19.
Exl, Lukas, et al.. (2012). Fast stray field computation on tensor grids. Journal of Computational Physics. 231(7). 2840–2850. 21 indexed citations
20.
Gusenbauer, Markus, et al.. (2011). Self-organizing magnetic beads for biomedical applications. Journal of Magnetism and Magnetic Materials. 324(6). 977–982. 8 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.

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