Summary
Lars Gebraad is an R&D engineer based in Zurich with nine years' experience developing full-waveform simulation and inversion tools for geoscience, nondestructive testing, and structural health monitoring. He builds physics-driven digital twins and scalable Bayesian inference pipelines that turn high-fidelity seismic, guided-wave, and ultrasonic models into practical inspection and monitoring solutions. His PhD work at ETH Zurich combined Hamiltonian Monte Carlo, MCMC, and machine learning on supercomputers to quantify uncertainty in PDE-constrained global seismology problems—skills he now applies to industrial diagnostics and composite inspection at Mondaic. Lars blends deep academic rigor with product-focused engineering, making him adept at delivering simulation-backed answers where conventional methods fail. An unusual strength is his track record of translating large-scale, uncertainty-aware inference into usable tools for both aerospace materials and subsurface imaging.
9 years of coding experience
Master's degree, Applied Geophysics, Cum Laude, Master's degree, Applied Geophysics, Cum Laude at RWTH Aachen University
TU Delft
Middelbare School, Nature & Technology, Middelbare School, Nature & Technology at Vechtdal College Hardenberg
Master's degree, Applied Geophysics, Cum Laude, Master's degree, Applied Geophysics, Cum Laude at Eidgenössische Technische Hochschule Zürich
Academic Minor, Geophysics, Mathematics, Physics, A-, Academic Minor, Geophysics, Mathematics, Physics, A- at The University of British Columbia
Dutch, English