Biography

I have been a graduate student at École Normale Supérieure de Lyon (ENS), a PhD student at the University of Milan, and a CERN fellow.

My research is mostly focussed on computational models and methods applied to science. I had the opportunity to perform scientific research in theoretical and experimental physics at different institutions. I had experience in quantum optics at the Institut Lumière Matière in Lyon, cavity quantum electrodynamics at the Laboratoire Kastler-Brossel (ENS) in Paris with the Nobel Price Serge Haroche, data analysis and software development for heavy-ion physics in ALICE at CERN, theoretical physics at CERN and UNIMI, and quantum computing scientific collaboration at the Quantum Research Centre.

Interests

  • Computational Physics
  • Parton Distribution Functions
  • Monte Carlo Simulation
  • Artificial Intelligence
  • Quantum Computing
  • AI & Medical Physics
  • Big data for Economics

Education

  • PhD in Physics, Astrophysics and Applied Physics

    University of Milan (Italy)

  • MSc in Sciences of Matter and Physics

    École Normale Supérieure (France)

  • BSc in Physics

    École Normale Supérieure (France)

Experience

Research

 
 
 
 
 

Researcher

University of Milan

Oct 2018 – Present Milan, Italy
 
 
 
 
 

Senior Research Fellow

CERN, Theoretical Physics Department

Oct 2015 – Sep 2018 Geneva, Switzerland
 
 
 
 
 

Postdoctoral Fellow

University of Milan

Nov 2014 – Sep 2015 Milano, Italy

Teaching

Ongoing lectures

 
 
 
 
 

Tecniche di calcolo e sistemi operativi - Spec. in Fisica Medica

University of Milan

Apr 2021 – Present Milan, Italy
 
 
 
 
 

Trattamento delle immagini - Spec. Medicina nucleare

University of Milan

Oct 2019 – Present Milan, Italy
 
 
 
 
 

Informatica - Laurea Triennale in Fisica

University of Milan

Oct 2018 – Present Milan, Italy

Registrazioni lezioni e risultati esami:

Sito corso:

 
 
 
 
 

Introduction to Machine Learning - PhD in Physics

University of Milan

Oct 2018 – Present Milan, Italy
An introduction to machine learning techniques including model representation, parameter learning, non-linear models, hyperparameter tune, and an overview of modern deep learning strategies. The seminars will cover the theoretical and mathematical aspects of machine learning followed by practical examples of code implementation using public frameworks.

Awards

Sergio Fubini

National price for the best PhD thesis in theoretical particle physics of 2015-2016.

Projects

Quantum

Quantum computation

MC tools

High energy physics simulation

PDFs

Parton distribution functions

Recent Publications

Qibo: a framework for quantum simulation with hardware acceleration

We present Qibo, a new open-source software for fast evaluation of quantum circuits and adiabatic evolution which takes full advantage …