ML for Engineering and Manufacturing

dida develops customized solutions for automating complex industry processes. A particular focus is on engineering workflows and manufacturing, where design and production processes are highly company-specific. In this area, we develop physics-informed and mathematical models that make processes more efficient and accurate. To this end, we have expertise in solving simulations using ML (e.g. through phyiscs-informed neural networks, neural operators, diffusion models), reinforcement learning, stochastic optimal control and edge computing. We are seeking collaborations to investigate new ML methods and innovative process optimizations in these areas.