Alessio Spurio Mancini

Alessio Spurio Mancini is a Lecturer in Physics at the Department of Physics, Royal Holloway, University of London. His primary research focuses on applying Machine Learning and statistical inference techniques to cosmology, particularly in analyzing weak gravitational lensing data from missions like the Euclid satellite. He leads the Euclid Consortium 3x2pt Work Package and developed the COSMOPOWER framework, a neural network-based tool for accelerated cosmological analysis.

• Education: PhD in Physics & Astronomy from Heidelberg University (2015–2018)

Research interests span cosmological emulation, neural network applications in astrophysics, and interdisciplinary uses of Machine Learning in fields like seismology. Current projects include the INTIME initiative exploring neutron star timing properties.

Key contributions include the COSMOPOWER library for Bayesian inference acceleration and publications on cosmological constraints using photometric probes.