Publications

Mimetic finite difference schemes for transport operators with divergence-free advective field and applications to plasma physics

M. Bassanini; S. Deparis; P. Ricci 

Journal of Computational Physics. 2026. Vol. 547, p. 114539. DOI : 10.1016/j.jcp.2025.114539.

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Deformable registration and generative modelling of aortic anatomies by auto-decoders and neural ODEs

R. Tenderini; L. Pegolotti; F. Kong; S. Pagani; F. Regazzoni et al. 

npj Biological Physics and Mechanics. 2025. Vol. 2, num. 1. DOI : 10.1038/s44341-025-00029-z.

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Model order reduction of hæmodynamics by space–time reduced basis and reduced fluid–structure interaction

R. Tenderini; S. Deparis 

Computer Methods in Applied Mechanics and Engineering. 2025. Vol. 447, p. 118347. DOI : 10.1016/j.cma.2025.118347.

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A spline-based hexahedral mesh generator for patient-specific coronary arteries

F. Marcinnò; J. Hinz; A. Buffa; S. Deparis 

Computer Methods in Applied Mechanics and Engineering. 2025. Vol. 445, p. 118153. DOI : 10.1016/j.cma.2025.118153.

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Computational fluid-structure interaction analysis of the end-to-side radio-cephalic arteriovenous fistula

F. Marcinno; C. Vergara; L. Giovannacci; A. Quarteroni; G. Prouse 

Computer Methods And Programs In Biomedicine. 2024. Vol. 249, p. 108146. DOI : 10.1016/j.cmpb.2024.108146.

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EQUITY AND EXAMINATION TIME PRESSURE IN FIRST YEAR MATHEMATICS FOR ENGINEERS

R. Tormey; A. Niculescu; H. Verma; C. Hardebolle; S. Deparis 

2024. 52 Conference of the European Society for Engineering, Lausanne, Switzerland, 2024-09-02 – 2024-09-05. p. 916 – 925. DOI : 10.5281/zenodo.14254730.

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Reluctance Despite Recognition: Student Perceptions of Benefits of Group Work

M. Pineros-Rodriguez; S. Deparis; K. Hess; J. de Lima 

2024. 52 Conference of the European Society for Engineering, Lausanne, Switzerland, 2024-09-02 – 2024-09-05. p. 2012 – 2022. DOI : 10.5281/zenodo.14256707.

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Reduced order models to address temporal complexity and geometrical variability in hemodynamics

R. Tenderini / S. Deparis (Dir.)  

Lausanne, EPFL, 2024. 

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SPACE-TIME REDUCED BASIS METHODS FOR PARAMETRIZED UNSTEADY STOKES EQUATIONS

R. Tenderini; N. Mueller; S. Deparis 

Siam Journal On Scientific Computing. 2024. Vol. 46, num. 1, p. B1 – B32. DOI : 10.1137/22M1509114.

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An exploratory analysis of student behaviour, performance and evaluation in hybrid and blended first year bachelor calculus course

A. S. Helsdingen; M. P. Rodriguez 

2024. 52 Conference of the European Society for Engineering, Lausanne, Switzerland, 2024-09-02 – 2024-09-05. p. 130 – 137. DOI : 10.5281/zenodo.14254906.

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DeepBND: A machine learning approach to enhance multiscale solid mechanics

F. Rocha; S. Deparis; P. Antolin; A. Buffa 

Journal of Computational Physics. 2023. Vol. 479, p. 111996. DOI : 10.1016/j.jcp.2023.111996.

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Can Knowledge Transfer Techniques Compensate for the Limited Myocardial Infarction Data by Leveraging Haemodynamics? An in silico Study

R. Tenderini; F. Betti; O. Y. Senouf; O. Muller; S. Deparis et al. 

2023. 21st International Conference on Artificial Intelligence in Medicine (AIME), Portoroz, SLOVENIA, 2023-06-12 – 2023-06-15. p. 218 – 228. DOI : 10.1007/978-3-031-34344-5_26.

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The INTERNODES method for applications in contact mechanics and dedicated preconditioning techniques

Y. Voet; G. Anciaux; S. Deparis; P. Gervasio 

Computers & Mathematics With Applications. 2022. Vol. 127, p. 48 – 64. DOI : 10.1016/j.camwa.2022.09.019.

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PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

R. Tenderini; S. Pagani; A. Quarteroni; S. Deparis 

SIAM Journal on Scientific Computing. 2022. Vol. 44, num. 3, p. B605 – B639. DOI : 10.1137/21M1438529.

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Gender, prior knowledge, and the impact of a flipped linear algebra course for engineers over multiple years

C. Hardebolle; H. Verma; R. Tormey; S. Deparis 

Journal of Engineering Education. 2022.  p. 1 – 21. DOI : 10.1002/jee.20467.

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Conservation of Forces and Total Work at the Interface Using the Internodes Method

S. Deparis; P. Gervasio 

Vietnam Journal of Mathematics. 2022. DOI : 10.1007/s10013-022-00560-9.

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Deep Neural Network to Accurately Predict Left Ventricular Systolic Function Under Mechanical Assistance

J. Bonnemain; M. Zeller; L. Pegolotti; S. Deparis; L. Liaudet 

Frontiers In Cardiovascular Medicine. 2021. Vol. 8, p. 752088. DOI : 10.3389/fcvm.2021.752088.

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On the preconditioning of the INTERNODES matrix for applications in contact mechanics

Y. Voet 

2021.

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Model order reduction of flow based on a modular geometrical approximation of blood vessels

L. Pegolotti; M. R. Pfaller; A. L. Marsden; S. Deparis 

Computer Methods in Applied Mechanics and Engineering. 2021. Vol. 380, p. 113762. DOI : 10.1016/j.cma.2021.113762.

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Reduction techniques for PDEs built upon Reduced Basis and Domain Decomposition Methods with applications to hemodynamics

L. Pegolotti / S. Deparis (Dir.)  

Lausanne, EPFL, 2021. 

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