Speaker
Michele Floris
(CERN)
Description
ALICE is the LHC experiment dedicated to the study of Heavy Ion collisions. In particular, the detector features low momentum tracking and vertexing, and comprehensive particle identification capabilities. In a single central heavy ion collision at the LHC, thousands of particles per unit rapidity are produced, making the data volume, track reconstruction and search of rare signals particularly challenging. Data science and machine learning techniques could help to tackle some of the challenges outlined above. In this talk, we will discuss some early attempts to use these techniques for the processing of detector signals and for the physics analysis. We will also highlight the most promising areas for the application of these methods.
