Scientific machine learning for extreme events

Faro Schäfer

As a doctoral researcher at ETH Zurich, I explore what scientific machine learning can reveal about tropical cyclones and the hazards they set off in the ocean. My aim is to bring this work into climate adaptation platforms, to make hazard estimates and risk assessments more reliable.

Extreme events have always been a passion of mine. My work sits where physics-based models meet machine learning, and making such models hold up in the real world is what I care about. Before the PhD, I worked at the Danish Hydraulic Institute (DHI), at the interface of R&D and client advisory, on storm-surge forecasting and on bringing modelling systems into reliable daily operation, mainly for ports and marine infrastructure.

Today, I continue this work alongside my doctoral research as an independent consultant for public authorities, industry and decision-makers.