REMOTE: Machine Learning for the LHC and future machines: applications for simulations and operation

About

Abstract

At the CERN Large Hadron Collider (LHC), several ML applications were actively pursued in view of assessing their potential benefits before making them an integral part of the accelerator operations and controls. These applications range from anomaly detection to pattern recognition and advanced data analysis. From a simulation perspective, machine learning can improve computational efficiency by extrapolating results or narrowing the search amongst many parameters. This lecture will explore the underlying techniques and show how they were used in the various applications.

Short Bio Gianluca Valentino

Dr Gianluca Valentino is a Senior Lecturer with the Department of Communications and Computer Engineering of the Faculty of ICT at the University of Malta. Previously, he spent 6 years at CERN for his PhD studies and was a post-doctoral fellow with the LHC Collimation Project. He still has an affiliation as a Visiting Scientist at CERN. His research interests are the development of machine learning and computer vision techniques for areas ranging from high energy physics to satellite imagery and bioinformatics.