IMOS x AI Center Seminar - AI for Science series - Prof. Johannes Brandstetter

The talk is jointly organized by the EPFL IMOS Lab and the EPFL AI Center.

Hosting professor: Prof. Olga Fink

Title
Closing the Gap Between Scientific Foundation Models and Real-World Applications

Abstract
In the era of LLM models, one gets notoriously confronted with the question of where we stand with applicability of large-scale deep learning models within scientific or engineering domains. The discussion starts by reiterating on recent triumphs in weather and climate modeling. Further, we discuss recent breakthroughs in fluid dynamics and related engineering fields, and subsequently extrapolate insights applicable to relatively untouched scientific and engineering fields. Finally, we outline challenges and potential solutions when it comes to scalability beyond traditional numerical schemes and discuss the respective impact on industry and scientific environments.

Bio: Prof. Johannes Brandstetter is leading a group “AI for data-driven simulations” at the Institute for Machine Learning at the Johannes Kepler University (JKU) Linz. Additionally, he's a Chief Researcher at NXAI - the new European AI hub in Linz (Austria). He has obtained his PhD after working several years at the CMS experiment at CERN. During this time, he had the privilege of learning from brilliant minds from all around the world, and got the chance to co-author seminal papers in the realm of Higgs boson physics. In 2018, after completing his PhD, his career trajectory shifted towards machine learning, and he was fortunate to join the research group of Mr LSTM Sepp Hochreiter in Linz. Under Sepp’s mentorship, he delved into the intricacies of machine learning and modern deep learning over a span of 2.5 years.