In the focus area “AI-assisted Engineering”, we combine the great potential of Artificial Intelligence (AI) with our domain knowledge to efficiently and accurately model, simulate, and optimize dynamical systems.

AI encompasses a large pool of methods that can be used in engineering to accelerate development processes, calculate complex phenomena, and predict the properties or behavior of systems and their components. The focus here is on Machine Learning (ML), which is a subset of AI and can draw conclusions from experimental or simulated data that are too difficult or costly for humans to formulate.

Conversely, classical approaches based on physics provide reliable and comparatively easy-to-understand predictions and are thus still of great value for, e.g., design decisions. Therefore, in many cases, we strive for a smart combination of AI and physics-based approaches.