Machine Learning for Detector R&D

by Prof. Fedor Ratnikov (National Research University - Moscow)

Aula C. Voci (Dipartimento di Fisica e Astronomia)

Aula C. Voci

Dipartimento di Fisica e Astronomia


The use of advanced machine learning techniques to speed up and improve the precision of the detector development and optimization cycle, with an emphasis on the experience and practical results obtained by applying this approach to optimizing the electromagnetic calorimeter design as a part of the upgrade project for the LHCb detector at LHC will be discussed.

Zoom link: https://cern.zoom.us/j/64604705321?pwd=SnZXRy9ndXBsYVNSaGgyam9BOXd2Zz09

Organized by

INFN Padova (S. Lacaprara, T. Dorigo)