Hinrichsen, Jan
Jan Hinrichsen, M. Sc.
Short Bio
Jan Hinrichsen studied mechanical engineering at the University of Stuttgart, where he received his bachelor’s degree in 2017. He continued his studies at the FAU and received his Master’s degree in 2020. During this time he also spent a semester abroad at the University of Tampere, Finland. Since 2021 he is pursuing his PhD and is employed as a research assistant at the Institute of Applied Mechanics and now at the Institute of Continuum Mechanics. His research focuses on mechanical modeling and simulation of human brain tissue. Specifically, he is working on material parameter identification from experiments conducted in our lab as well as modeling brain folding using finite element models.
When he is not in the office, he can be found exploring nature on his mountain bike or volunteering for the German Federal Agency for Technical Relief (THW).
2024
Model-driven exploration of poro-viscoelasticity in human brain tissue: be careful with the parameters!
In: Interface Focus 14 (2024)
ISSN: 2042-8901
DOI: 10.1098/rsfs.2024.0026
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Identifying composition-mechanics relations in human brain tissue based on neural-network-enhanced inverse parameter identification
In: Mathematics and Mechanics of Solids (2024)
ISSN: 1081-2865
DOI: 10.1177/10812865231206544
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Using dropout based active learning and surrogate models in the inverse viscoelastic parameter identification of human brain tissue
In: Frontiers in Physiology 15 (2024), Article No.: 1321298
ISSN: 1664-042X
DOI: 10.3389/fphys.2024.1321298
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2023
Multilayer 3D bioprinting and complex mechanical properties of alginate-gelatin mesostructures
In: Scientific Reports 13 (2023), p. 11253-
ISSN: 2045-2322
DOI: 10.1038/s41598-023-38323-2
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Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID
In: Journal of the Mechanics and Physics of Solids 180 (2023), Article No.: 105404
ISSN: 0022-5096
DOI: 10.1016/j.jmps.2023.105404
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On the importance of using region-dependent material parameters for full-scale human brain simulations
In: European Journal of Mechanics A-Solids 99 (2023), Article No.: 104910
ISSN: 0997-7538
DOI: 10.1016/j.euromechsol.2023.104910
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Inverse identification of region-specific hyperelastic material parameters for human brain tissue
In: Biomechanics and Modeling in Mechanobiology (2023)
ISSN: 1617-7959
DOI: 10.1007/s10237-023-01739-w
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Inverse identification of region-specific hyperelastic material parameters for human brain tissue
In: Biomechanics and modeling in mechanobiology (2023)
ISSN: 1617-7940
DOI: 10.1007/s10237-023-01739-w
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Poro-viscoelastic material parameter identification of brain tissue-mimicking hydrogels
In: Frontiers in Bioengineering and Biotechnology 11 (2023), Article No.: 1143304
ISSN: 2296-4185
DOI: 10.3389/fbioe.2023.1143304
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2022
Tissue-Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models
In: Current Protocols 2 (2022), p. e381-
ISSN: 2691-1299
DOI: 10.1002/cpz1.381
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Laboratory Training Biomechanics
since 2023