Published multiple research papers covering topics such as neural network models for incompressible hyperelasticity, inverse design of anisotropic microstructures using physics-augmented neural networks, a hybrid fracture model combining neural networks with phase-field, etc.
Research Experience
Postdoc in GRK 2868 D3 Graduate School.
Education
No specific educational background information provided.
Background
Research interests include data-driven simulation techniques, application of neural networks in solid mechanics, modeling and simulation of magnetically active materials, nonlinear FEM, homogenization methods, coupled field problems, material modeling, parameter identification, and characterization and reconstruction of microstructures.
Miscellany
Teaches 'Material Theory' in the summer semester, 'Multiscale Numerical Modeling' in the winter semester, and supervises exercises in both basic and advanced study programs.