Research

Research and Academia

Gravitational-wave science, data analysis, and artificial intelligence for complex physical systems.

Research focus

  • Gravitational waves
  • Virgo
  • Detector characterization
  • Noise analysis
  • Machine learning
  • Artificial intelligence
  • Signal detection

My research focuses on gravitational-wave data analysis, detector characterization, and the development of machine learning and AI methods for extracting weak astrophysical signals from complex and noisy data. I am a member of the LIGO/Virgo/KAGRA Collaboration.

Academic positions

  • 2024 – present

    Full Professor

    University of Bologna

  • 2018 – 2024

    Head of the Data Science Office

    European Gravitational Observatory

  • 2018 – 2024

    Associate Faculty

    Scuola Normale Superiore

Leadership and coordination

  • 2008 – 2014

    Group Leader, Virgo Noise Analysis Group

    Led the noise-analysis effort within the Virgo Collaboration.

  • 2014 – 2018

    Scientific Coordinator, GraWIToN ITN

    Initial Training Network educating early-career researchers in gravitational-wave science.

  • 2018 – 2023

    Main Proposer & Action Chair, COST Action CA17137 (G2Net)

    A Network for Gravitational Waves, Geophysics, and Machine Learning.

  • 2018 – 2023

    Co-chair, Machine Learning informal group

    LIGO–Virgo–KAGRA Collaboration.

  • 2019 – 2021

    General Assembly Chair & Contributor, ESCAPE Project

    European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures.

  • 2021 – 2023

    Extreme Universe Science Project Coordinator, EOSC-Future

    European Open Science Cloud.

  • 2021 – 2025

    Co-Chair, Einstein Telescope Data Analysis Division

    Data quality assessment and noise-mitigation strategy for the ET data-analysis platform.

  • 2021 – 2025

    Member, CTAO Scientific & Technical Advisory Committee

    Cherenkov Telescope Array Observatory.

  • 2024 – present

    Virgo DIFA–INFN Bologna Group Leader

    Head of the joint DIFA–INFN Virgo Collaboration group, University of Bologna.

  • 2026 – present

    Coordinator, Data Analysis & AI Work Package, CAOS Laboratory

    International laboratory for gravitational-wave and seismology applications, University of Perugia — part of the Einstein Telescope Infrastructure Consortium (ETIC).

Honors

2016 Special Breakthrough Prize in Fundamental Physics

Awarded to the LIGO–Virgo–KAGRA Collaboration for the discovery of gravitational waves.

2016 Gruber Cosmology Prize

Awarded to the LIGO–Virgo–KAGRA Collaboration.

Projects and networks

COST Action CA17137 (G2Net)

A European network connecting gravitational-wave physics, geophysics, and machine learning.

COST page G2Net

GraWIToN ITN

Initial Training Network for early-career researchers in gravitational-wave science.

Cordis project page

ESCAPE Project

European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures.

Project website

EOSC-Future

Extreme Universe Science Project, within the European Open Science Cloud.

Project website

Selected publications

Gravitational Wave Science with Machine Learning

Springer, book (2025)

View book

Applications of machine learning in gravitational-wave research with current interferometric detectors

Living Reviews in Relativity (2025)

Read paper

Machine learning for gravitational-wave science

Machine Learning: Science and Technology (2021)

Read paper

Full list on Google Scholar

Editorial roles and community

Editorial boards

  • Machine Learning: Science and Technology (IOP)
  • MDPI Signals
  • Loop Frontiers — Efficient AI in Particle Physics & Astrophysics

EuCAIF — European Coalition for Artificial Intelligence in Fundamental Physics

Co-founder & Management Board member

Visit EuCAIF

Public engagement

TEDxPutignano — "Un'onda nel caos"

Talk on gravitational waves and discovery, for a general audience.

Watch talk

Kaggle Master

Public profile with machine-learning competitions, including the g2net gravitational-wave challenges.

Kaggle profile

Teaching and mentorship

I supervise and mentor undergraduate, master's, and Ph.D. students on projects related to data analysis, statistical inference, and machine learning for gravitational-wave science.

  • Data analysis and statistical methods for physics
  • Machine learning for time series
  • Research training in international networks and schools