<u>Learning the onset of frictional motion</u>

The onset of frictional motion is a central process in modeling mechanical phenomena, from squeaking hinges to catastrophic earthquakes. The processes involved in it are complex and to a large extent not understood. Specifically, the simple notion of "static friction coefficient" is most probably not a well-defined material parameter, as experiments show that it is variable, even for a single interface under carefully controlled experimental conditions. I will show that, in a well-controlled laboratory setup with detailed interfacial measurements, relatively simple linear models can explain much of the observed variance, indicating that a significant portion of the uncertainty is non-stochastic and is encoded in the frictional interface. In addition, I will discuss recent data-driven efforts in predicting the onset of frictional motion in geophysical faults, i.e. earthquake forecasting, which is a long-standing and very challenging problem. However, the confluence of new kinds of measurements and advances in machine learning offers new and promising directions.