Following the preparation for the High Luminosity era of the Large Hadron Collider (LHC) and the imminent increase on the
frequency of collisions by one order of magnitude it is evident the need for the development and implementation of new tools to
optimize several tasks such as particle identification, reconstruction, data storage and processing.
Many of these implementations will be based on machine learning algorithms that have the potential to process signals in a
smarter way than current technologies allowing to fully exploit the detector capabilities of the LHC experiments and increase
the probability to find new physics phenomena.