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1. Kabus, D., Arno, L., Leenknegt, L., Panfilov, A. V., & Dierckx, H. (2022). Numerical methods for the detection of phase defect structures in excitable media. PLOS ONE, 17(7), 1–31. https://doi.org/10.1371/journal.pone.0271351
2. Cloet, M., Arno, L., Kabus, D., Van der Veken, J., Panfilov, A. V., & Dierckx, H. (2023). Scroll waves and filaments in excitable media of higher spatial dimension. Physical Review Letters, 131(20), 208401. https://doi.org/10.1103/PhysRevLett.131.208401
3. Kabus, D., De Coster, T., de Vries, A. A. F., Pijnappels, D. A., & Dierckx, H. (2024). Fast creation of data-driven low-order predictive cardiac tissue excitation models from recorded activation patterns. Computers in Biology and Medicine, 169, 107949. https://doi.org/10.1016/j.compbiomed.2024.107949
4. Kabus, D., Cloet, M., Zemlin, C., Bernus, O., & Dierckx, H. (2024). The Ithildin library for efficient numerical solution of anisotropic reaction-diffusion problems in excitable media. PLOS ONE, 19(9), 1–26. https://doi.org/10.1371/journal.pone.0303674
5. Legat, T., Grachev, V., Kabus, D., Lettinga, M. P., Clays, K., Verbiest, T., de Coene, Y., Thielemans, W., & Van Cleuvenbergen, S. (2024). Imaging with a twist: Three-dimensional insights of the chiral nematic phase of cellulose nanocrystals via SHG microscopy. Science Advances, 10(44), eadp2384. https://doi.org/10.1126/sciadv.adp2384
6. Arno, L., Kabus, D., & Dierckx, H. (2024). Analysis of complex excitation patterns using Feynman-like diagrams. Scientific Reports, 14(1), 28962. https://doi.org/10.1038/s41598-024-73544-z
7. Arno, L., Kabus, D., & Dierckx, H. (2025). Strings, branes and twistons: Topological analysis of phase defects in excitable media such as the heart. Physical Review Letters, 135(12), 128402. https://doi.org/10.1103/5pgp-1wj6
8. Gobeyn, A., Kabus, D., Tolkacheva, E. G., & Dierckx, H. (2025). ZEUS: Numerical methods to detect quasi-particles describing excitable media. Chaos: An Interdisciplinary Journal of Nonlinear Science, 35(12), 123105. https://doi.org/10.1063/5.0288713
9. Kabus, D., Dierckx, H., & De Coster, T. (2026). Pigreads: The Python-integrated GPU-enabled reaction-diffusion solver using OpenCL for cardiac electrophysiology and other applications. Computer Physics Communications, 110088. https://doi.org/10.1016/j.cpc.2026.110088

Im Erscheinen

1. De Coster, T., Kabus, D., Verkerk, A. O., Veldkamp, M. W., Harlaar, N., Dekker, S. O., Vries, A. A. F. de, Pijnappels, D. A., & Panfilov, A. V. (2026). Ionic mechanisms underlying human immortalised atrial action potential properties: Insights from a mathematical model.
2. Kamphuis, J. M., Kabus, D., Bonnet, S., Hupkes, H. J., & De Coster, T. (2026). Microscopic variability alters macroscopic rotation speed in stochastic spiral waves.
3. Leenknegt, L., Omara, S., Cloet, M., Kabus, D., Zeppenfeld, K., Panfilov, A. V., & Dierckx, H. (2026). The EGM generated by an oblique wave front and its application in solving the inverse problem.

Abschlussarbeiten

1. Kabus, D. (2016). Comparison of phase field and interpolation methods for the representation of geometries in the numerical analysis of reaction-diffusion systems [Bachelor’s thesis, Ruhr-Universität Bochum]. https://hbz-ubo.primo.exlibrisgroup.com/permalink/49HBZ_UBO/mnkbqv/alma991012283309706471
2. Kabus, D. (2019). Analysis of parametric level set functions for the representation of geometry in the optimal control of reaction-diffusion systems [Master’s thesis, Ruhr-Universität Bochum]. https://hbz-ubo.primo.exlibrisgroup.com/permalink/49HBZ_UBO/mnkbqv/alma991018264849706471
3. Kabus, D. (2025). Towards data-driven generation of individualised human heart models from scalable heart muscle sheets [PhD thesis, KU Leuven; Leiden University Medical Center]. https://dkabus.gitlab.io/thesis-phd

Konferenzbeiträge

1. Kabus, D., Arno, L., Leenknegt, L., Harlaar, N., Dekker, S. O., Panfilov, A. V., De Vries, A. A. F., Pijnappels, D. A., & Dierckx, H. (2022). Centres of spiral waves can be detected as phase defect lines in optical voltage mapping data and numerical simulations. Conference of the European Heart Rhythm Association (EHRA). https://esc365.escardio.org/presentation/247532
2. Kabus, D., Harlaar, N., Dekker, S. O., de Vries, A. A. F., Pijnappels, D. A., & Dierckx, H. (2023). Creation of predictive cardiac excitation models at the tissue scale with machine learning in augmented state space. SIAM Conference on Applications of Dynamical Systems (DS23). https://meetings.siam.org/sess/dsp_talk.cfm?p=127148
3. Kabus, D., & De Coster, T. (2025). Pigreads enables rapid scientific prototyping through integration into the Python ecosystem. Dynamics Days Europe 2025. https://websites.auth.gr/ddeu2025/wp-content/uploads/sites/321/2025/06/Kabus.pdf
4. Kabus, D., Dierckx, H., & De Coster, T. (2025). Accelerated simulation of cardiac tissue using data-driven models. Conference on Mathematics of Wave Phenomena 2025. https://conference25.waves.kit.edu/wp-content/uploads/2025/02/BoA.pdf