She has been working on Data Analysis for Virgo experiment since more than 20 years.
After degree in Physics on Statistical Analysis in Astrophysics for Large Scale Structure of the Universe, she won a PhD fellowship at Physics Department in Pisa and started working for Virgo experiment. She is expert in noise analysis and system identification, developing algorithms for data conditioning and signals detection. She leaded the noise analysis group for Virgo from 2008 to 2014, developing algorithms for data characterization and for the analysis of transient signals and working with machine learning techniques in this field.
From 2014 to 2018 she was the Scientific Coordinator on an Initial Training Network GraWIToN, addressed to the training of young scientist in Gravitational Wave research.
She is co-chair of the Machine Learning informal group in the LIGO/Virgo collaboration. She is Kaggle master. She was the main proposer for a COST action “A network for Gravitational Waves, Geophysics and Machine Learning”, which was financed by COST association. Now she is Cost Action 17137 chair.