Christopher Straub

I am a Senior Scientist at the AI-augmented Simulation group at Fraunhofer IISB in Erlangen (Germany). I am leading the research activities on Scientific Machine Learning, focusing on

Physics-Informed Machine Learning and its industrial applications,
methodological improvements of Physics-Informed Neural Networks.

My work spans diverse industry-relevant applications, including semiconductor process simulations, lithography, battery modelling, and plastic deformation.

I have a background in mathematics, where I obtained my PhD in March 2024. My doctoral research was focused on the analysis of partial differential equations arising in galactic dynamics using mathematical and numerical methods.

Recent news:

Mar 10, 2026	Our paper Physics-informed fine-tuning of foundation models for partial differential equations has been accepted at the ICLR 2026 Workshop on Artificial Intelligence and Partial Differential Equations. Very excited about this new research direction led by Vlad Medvedev and Leon Armbruster.
Mar 03, 2026	I attended the German Crystal Growth Conference again to give talks about our work on physics-informed machine learning for coupled heat transport problems and AI-based wafer defect detection.
Feb 03, 2026	Our paper Towards a simulation model for pneumatic conveying of cable-like deformable linear objects is available via IEEE Xplore. Another great collaboration with FAPS (Simon Fröhlig, Patrick Bründl, and Jörg Franke)!
Feb 01, 2026	New preprint available online: Physics-Informed Operator Learning for Parameter Estimation in Lithium-Ion-Battery Models Enhanced by Global Experimental Design and Local Identifiability Analysis. Led by Philipp Brendel; joint work with Andreas Rosskopf, Vincent Lorentz, and Felix Dietrich.
Jan 26, 2026	I gave a one hour talk titled Bridging numerics and scientific machine learning for industrial applications within the FAU MoD Lecture Series. [Webpage]