Curriculum Vitae

Luciano Maria Barone

Associate Professor in experimental physics (FIS01)



the CMS experiment at LHC and the INFN-Roma Tier-2 computing centre.


November 1981: Researcher at Università di Roma "La Sapienza";
August 1981-December 1983: Fellow at CERN, Geneva;
November 2000: Associate Professor at Università di Roma "La Sapienza";
2005: Scientific Associate at CERN, Geneva.


Neutrino experiments

I worked in the CHARM collaborationon neutrino experiments, contributing to the study of the inverse muon decay, the beam dump experiment and search for neutrino oscillations

L3 experiment at LEP

In the L3 Collaboration I was responsible for the calibration database of the experiment designed by me with two colleagues. I collaborated to the calibration of the BGO ECAL calorimeter in the Rome group. I worked in the Higgs research group.

CMS experiment at LHC

I am currently working in the CMS experiment with the Rome group, I contributed to the construction of the ECAL calorimeter. I had several relevant roles in the experiment computing (see below).


In the CMS experiment I have been world responsible for the MC data production from 2005 to 2007, coordinating an international group of about 30 people.

I am the responsible of the new INFN-Roma-CMS Tier-2 computing centre: I have designed the structure of the centre, taken all the strategic decisions to set it up and make it operational. I coordinate a group of about five people participating to this activity.
The centre was relevant for the data analysis which brought to the discovery of the Higgs boson in 2012.

Other activities

I have worked in collaboration with Unione Industriali Roma to set up and give basic and advanced courses on Linux for professionals.


I am co-author of about 450 scientific papers (see here for a list), including the fundamental paper on the Higgs discovery..

I am co-author of the book:


Programming skills

C, FORTRAN, Perl, PHP, Java.

Software skills

Linux, MySQL.

Other skills

Automation, data acquisition, treatment of large data samples, computing farms.