Federica Lionetto

Federica Lionetto, Dr

Former member (PhD student)

I completed my master in physics at the University of Pisa (Italy) in 2013. While at university, I worked as a summer student for the CDF and NA62 experiments, and as a technical student for the LHCb experiment. 
 
After graduating, I started a PhD at the University of Zurich (Switzerland), where I worked on the data analysis of rare decays of bottom hadrons, and on R&D and testing activities in view of the upgrade of the tracking system of the LHCb detector.
The data analysis focused on the first measurement of the difference between the angular observables of the B0->K*0mm and B0->K*0ee decays using the data set collected by the LHCb detector. The interest toward this measurement had significantly increased in recent years, after hints of deviations from the Standard Model predictions were observed in the angular distribution of the B0->K*0mm decay as well as in the branching fraction ratios between muons and electrons. The results of this measurement, which are compatible with the Standard Model predictions and dominated by statistical uncertainties, are important to show the capabilities of the LHCb experiment and provide a baseline for upcoming measurements.
The R&D and testing activities consisted in dedicated measurements on prototype silicon micro-strip sensors performed with beams of particles at the CERN Super Proton Synchrotron and allowed to characterize the long-term performance of the sensors before production.
 
The possibility of being involved in both data analysis and experimental measurements at the forefront of research in particle physics and the presence of an inspiring team allowed me to grow my skills in areas like machine learning, statistics and simulation. 
 
In 2018, after completing my PhD, I started a new adventure in the world of business. I work as a data scientist in the data analytics team of a global consulting firm. My work focuses on predictive healthcare and personalized medicine, as well as data analysis relevant for the life science industry.