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Biography
My research focuses on applications of Machine Learning and statistical inference techniques to cosmology and beyond.
I combine these techniques into pipelines for the extraction of cosmological information from cutting-edge astronomical data. In particular, I focus on constraints on the “Dark Universe” from weak gravitational lensing data, as measured by optical galaxy surveys like ESA’s Euclid satellite mission, for which I lead the 3x2pt Work Package in the Weak Lensing Science Working Group.
I am the creator of COSMOPOWER, a Machine Learning framework for accelerated statistical inference with neural emulators. COSMOPOWER is publicly available at:
https://github.com/alessiospuriomancini/cosmopower
I also like to apply advanced Machine Learning and statistical inference to interesting problems beyond cosmology and astrophysics — such as in seismology, to study earthquakes from their recorded seismic traces.
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Works (50 of 62)
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