During this period, my passion for Geometric Deep Learning, particularly involving Geometric (Clifford) algebras, and my interest in partial differential equations (PDEs), with a particular focus on developing neural surrogates for (PDEs), became profound. Most importantly, I pivoted towards large-scale PDEs, including weather and climate modeling.

My years in Amsterdam have shaped my research vision. I am firmly convinced that AI is on the cusp of disrupting simulations at industry-scale. Every day thousands and thousands of compute hours are spent on turbulence modeling, simulations of fluid or air flows, heat transfer in materials, traffic flows, and many more. Many of these processes follow similar underlying patterns, but yet need different and extremely specialized softward to simulate. Even worse, for different parameter settings the costly simulations need to be run at full length from scratch.

This is what I want to change! Therefore, I have started a new group at JKU Linz which has strong computer vision, numerical simulation, and engineering components. We want to advance data-driven simulations at industry-scale, and place the Austrian industry engine Linz as a center for doing that.