Numerical Machine Learning: Where Physics Meets AI

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

new.siemens.com/global/en/company/topic-areas/…

Oliver Niggemann

hsu-hh.de/ims/team/niggemann

Helmut Schmidt University (University of the Armed Forces Hamburg)

hsu-hh.de

KISS Project

dlr.de/rd/en/desktopdefault.aspx/tabid-2441/35…

Airbus Defence and Space

airbus.com/en/products-services/space

International Space Station (ISS) Columbus Module

esa.int/ScienceExploration/HumanandRoboticExpl… (esa.int/Science_Exploration/Human_and_Robotic_…)

Fraunhofer IOSB

iosb.fraunhofer.de

Physics-Informed Neural Networks (PINNs)

en.wikipedia.org/wiki/Physics-informedneuralne… (en.wikipedia.org/wiki/Physics-informed_neural_…)

Surrogate Models

en.wikipedia.org/wiki/Surrogate_model

Cusp.ai

cusp.ai

Jeffrey Hinton

en.wikipedia.org/wiki/Geoffrey_Hinton

Yann LeCun

en.wikipedia.org/wiki/Yann_LeCun

DeepMind Protein Folding (AlphaFold)

deepmind.com/research/highlighted-research/alp…