Discover how engineering, simulation, and AI converge to shape tomorrow’s breakthroughs. Why combining math and machine learning changes everything.

In this episode, I sit down once again with Professor Oliver Niggemann to unravel the world of numerical machine learning—where traditional engineering meets cutting-edge AI. We explore real-world projects from diagnosing the International Space Station to designing safer bridges, smarter batteries, and even optimizing biodiversity. Oliver breaks down how fusing symbolic knowledge and neural networks is revolutionizing simulation, design, and problem-solving across industries.

If you’ve ever wondered how AI can speed up material discovery or what the future holds for interdisciplinary engineers, this conversation is for you. We dive into the power of surrogate models, the evolution of engineering education, and why tomorrow’s innovations demand both deep technical expertise and creative collaboration. Join us for a look at the next frontier in industrial AI.

Siemens

https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html

Oliver Niggemann

https://www.hsu-hh.de/ims/team/niggemann/

Helmut Schmidt University (University of the Armed Forces Hamburg)

https://www.hsu-hh.de/

KISS Project

https://www.dlr.de/rd/en/desktopdefault.aspx/tabid-2441/3587_read-5637/

Airbus Defence and Space

https://www.airbus.com/en/products-services/space

International Space Station (ISS) Columbus Module

https://www.esa.int/ScienceExploration/HumanandRoboticExploration/Columbus

Fraunhofer IOSB

https://www.iosb.fraunhofer.de/

Physics-Informed Neural Networks (PINNs)

https://en.wikipedia.org/wiki/Physics-informedneuralnetworks

Surrogate Models

https://en.wikipedia.org/wiki/Surrogate_model

Cusp.ai

https://www.cusp.ai/

Jeffrey Hinton

https://en.wikipedia.org/wiki/Geoffrey_Hinton

Yann LeCun

https://en.wikipedia.org/wiki/Yann_LeCun

DeepMind Protein Folding (AlphaFold)

https://www.deepmind.com/research/highlighted-research/alphafold