Jonas Lindemann
Jonas Lindemann, Director at LUNARC. Jonas has a background in Structural Mechanics where he worked on distributed finite element applications, new user interface concepts for engineering application as well as visualisation of material behavior in mechanical simulations. Since 2004 he has been working at LUNARC designing, implementing and operating HPC resources for Lund University. He is also actively engaged in teaching scientific computing (Python, C++ and Fortran) for graduate as well as post graduate students. At LUNARC he has been the main developer of GfxLauncher and multiple other HPC related tools (ARC Storage Explorer, LUNARC Application portal and ml-browse a graphical module browser for lmod).
Session
Python has made it easy for engineers and scientists to turn equations into computational models. NumPy, SciPy, and domain-specific libraries such as CALFEM can take us from a mathematical formulation to working code in very few lines. But turning that model into a usable application—with an interface, visualisation, documentation, and reports—has traditionally required a much broader set of software-development skills.
Large language models are changing this workflow.
In this talk I will explore an AI-assisted engineering workflow built around a small, Python computational core. Using a structural mechanics example implemented in NumPy and CALFEM, we develop and verify an engineering model and then use an LLM to help create the software surrounding it: user interaction, visualisation, result presentation, and reporting.
The interesting question is not whether AI can write Python. It clearly can. The question is how we divide responsibility between the engineer and AI.
I will argue for a simple principle: the engineer owns the model and its validation; AI can help build the application and tools around it.
This approach has implications not only for engineering software development, but also for how we teach Python to future engineers and scientists.