Dr.-Ing. Lukas Bruder
Contact
Research interests
- Biomechanical Modeling and Simulation
- Uncertainty Quantification
- Inverse Problems
- Surrogate modeling
- Bayesian methods
- Machine Learning & Statistical analysis
Academic background
| 04/2017 - 09/2021 | Research associate, Mechanics & High Performance Computing Group, Technical University of Munich, Germany |
08/2018 - 10/2018 02/2017 | Visiting researcher, Optimization & Uncertainty Quantification Department, Sandia National Labs, Albuquerque, USA Master of Science (M.Sc.) in Mechanical Engineering, Technical University of Munich, Germany |
PhD Thesis
- Bruder, L. (2022): Biomechanical assessment of abdominal aortic aneurysm rupture risk and growth using clinical data: a probabilistic approach, https://mediatum.ub.tum.de/1639063
Peer-Reviewed Journal Articles
- Bruder, L., Pelisek, J., Eckstein, H.-H., Gee, M.W. (2020): Biomechanical rupture risk assessment of abdominal aortic aneurysms using clinical data: a patient-specific, probabilistic framework and comparative study, PLOS ONE, 10.1371/journal.pone.0242097
- Bruder, L., Gee, M.W., Wildey, T. (2020): Data-consistent Solutions to Stochastic Inverse Problems using a Probabilistic Multi-fidelity Method Based on Conditional Densities, International Journal for Uncertainty Quantification, 10.1615/Int.J.UncertaintyQuantification.2020030092
- Bruder, L., Reutersberg, B., Bassilious, M., Schüttler, W., Eckstein, H.-H., Gee, M.W. (2019): Methoden der künstlichen Intelligenz in der vaskulären Medizin - Status quo und Ausblick am Beispiel des AAAs, Gefässchirurgie, 10.1007/s00772-019-00574-7
- Bruder, L., Koutsourelakis, P.S. (2018): Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography, International Journal for Uncertainty Quantification, 10.1615/Int.J.UncertaintyQuantification.2018025837
Conference Contributions with Abstract
- Bruder, L., Pelisek, J., Eckstein, H.-H., Gee, M.W.: A data-informed, patient-specific framework for the quantification of abdominal aortic aneurysm rupture risk, WCCM-ECCOMAS Virtual Congress, January 11-15, 2021
- Bruder, L., Wildey, T.M., Pelisek, J., Eckstein, H.-H., Gee, M.W.: Parameter identification and uncertainty quantification for the predictive simulation of abdominal aortic aneurysm growth, UNCECOMP - International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Crete, Greece, June 24-26 2019
- Bruder, L., Pelisek, J., Eckstein, H.-H., Gee, M.W.: Towards fully patient-specific non-invasive rupture risk estimation of abdominal aortic aneurysms, ECCM - European Conference on Computational Mechanics, Glasgow, UK, June 11-15, 2018
Teaching
- Engineering Mechanics 1 Exercises
- Engineering Mechanics 2 Exercises