Scientific Organisers

Pieter Glatzel, ESRF
Marius Retegan, ESRF
Mauro Rovezzi, ESRF
Christoph Sahle, ESRF
Guillaume Morard, ISTerre, France (UOC representative)
Alberto Martinelli, CNR-SPIN Genoa, Italy (UOC representative)
Keynote Speakers

Thomas Penfold, Newcastle University, UK
Nongnuch Artrith, Utrecht University, Netherlands
Johannes Niskanen, University of Turku, Finland
Matthew Newville, University of Chicago, USA
Administrative Assistant Eva Jahn
Contact udm2-um24@esrf.fr
Venue ESRF - Auditorium


Final Programme
 

AIM & SCOPE

_______

 

Machine learning (ML) is increasingly used in natural sciences to exploit large amounts of data. Applications include a wide range of domains, from fundamental research in chemistry, biology, and materials science to the optimization of experimental pipelines and self-driven experiments. The user-dedicated microsymposium aims to present the current state of the art and future developments of ML in the field of X-ray spectroscopy, with an additional focus on the experimental data curation and its use in ML applications.