Lukas Exl

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Universität Wien

Austria

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Recent Grants

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Design of Nanocomposite Magnets by Machine Learning

Open Date: 2022-11-01

Close Date:

Grant: Close

Reduced Order Approaches for Micromagnetics (ROAM)

Open Date: 2018-10-01

Close Date:

Articles (12)

Year:

2025

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2025

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2024

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2024

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2023

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2022

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2022

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2022

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2021

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2021

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2020

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2020

Collaborators (4)

Markus Gusenbauer

Donau-Universität Krems

AUSTRIA

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Dieter Suess

Professor

Universität Wien

AUSTRIA

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Thomas Schrefl

University for Continuing Education Krems

AUSTRIA

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Michele Ruggeri

University Of Strathclyde

UNITED KINGDOM

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Lukas Exl

Research Interests

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Contact this professor

Recent Grants

Articles (12)

Physics aware machine learning for micromagnetic energy minimization: Recent algorithmic developments

Explainable machine learning and feature engineering applied to nanoindentation data

Image-based prediction and optimization of hysteresis properties of nanocrystalline permanent magnets using deep learning

Constraint free physics-informed machine learning for micromagnetic energy minimization

Physics-informed machine learning and stray field computation with application to micromagnetic energy minimization

Magnetostatics and micromagnetics with physics informed neural networks

Bridging Fidelities to Predict Nanoindentation Tip Radii Using Interpretable Deep Learning Models

Conditional physics informed neural networks

Machine learning methods for the prediction of micromagnetic magnetization dynamics

Prediction of magnetization dynamics in a reduced dimensional feature space setting utilizing a low-rank kernel method

Computational micromagnetics with Commics

Learning time-stepping by nonlinear dimensionality reduction to predict magnetization dynamics

Collaborators (4)

Markus Gusenbauer

Dieter Suess

Thomas Schrefl

Michele Ruggeri

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