Christian Legaard is a machine learning engineer with a decade of experience marrying scientific modeling and ML to accelerate and integrate physics-based simulations. He earned a PhD focused on neural ODEs and physics-informed networks and built tooling to embed Python-based data-driven models into FMI-compliant industrial simulators, enabling safer digital-twin and systems engineering workflows. His research spans constrained optimization frameworks (contributing to PyTorch-based neuromancer interoperability) and reduced-order modeling for PDE-driven systems, with collaborative visits to PNNL and École Centrale de Nantes. Based in Aarhus, he combines rigorous mathematical grounding with hands-on software design and teaching experience, and—less expectedly—spent 18 months post-PhD traveling the world pursuing wildlife and underwater photography, scuba diving and climbing.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Software Engineering, Doctor of Philosophy - PhD, Computer Software Engineering at Aarhus University
Bachelor of Engineering - BE, Electrical and Electronics Engineering, Bachelor of Engineering - BE, Electrical and Electronics Engineering at Aarhus Universitet
Contributions:3 releases, 446 commits, 36 PRs in 1 year
fmi-supportpythonfmufunctional-mocksimulation
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Christian Legaard - Machine Learning Engineer at Aarhus University