Xmas seminar on ML@CERN

Christmas seminar was given on 13th December by Prof. Borut Paul Kerševan from "Jožef Stefan" Institute (JSI).

Title: Application of Machine Learning in High Energy Physics at CERN, past, present and future

Abstract: Prof. Borut Kerševan presented the diverse use of Machine Learning tools and approaches in High Energy Physics. He focused on the practices of the experiments at the Large Hadron Collider (LHC) at CERN. The LHC experiments use Machine Learning in a wide range of applications. These range from straightforward procedures of trying to differentiate the new physics and known processes in data analysis using e.g. deep neural networks, to using Machine Learning to replace traditional Monte Carlo simulation of physics processes.

State-of-the-art attempts comprise using programmable FPGA chips to implement very fast Machine Learning tools in detector operations, exploring the use of Machine Learning algorithms on Quantum Computers, employ Artificial Inteligence approaches to design the new generations of experiments, solve theoretical equations etc…

Special emphasis was given to the implementation of the transfer of latest commercial approaches, such as generative modelling, into scientific procedures with advantages they bring as well as associated caveats.  At the end his vision of the future of Machine Learning in HEP was presented.

The video of lecture is available here: ML@CERN