Judit Prat Marti
Former Eric and Wendy Schmidt AI in Science Postdoctoral Fellow
The world is rapidly entering the era of big data Cosmology. Modeling and observational systematics are limiting current analyses, with statistical uncertainties already being subdominant. Moreover, computing and technical challenges related to processing such large amounts of data are arising at different stages of the analysis. During this fellowship, Judit Prat Marti is planning to use novel AI techniques to extract more cosmological information from galaxy surveys. In particular, Judit Prat Marti will focus on applying machine learning methods to extract non-gaussian information from weak lensing maps from the Dark Energy Survey.
Judit Prat Marti was a Schmidt AI in Science Postdoctoral fellow at the University of Chicago, where Prat Marti was part of the Survey Science Group since 2019. Before being a researcher at the University of Chicago Prat Marti completed a PhD at the Autonomous University of Barcelona. Prat Marti is interested in obtaining cosmological information from the late-time Universe with galaxy surveys, in particular with galaxy clustering and weak gravitational lensing measurements. These direct cosmological measurements from the late-time Universe can be compared with the predictions from the current Standard Cosmological Model (LCDM) assuming the initial cosmological parameters measured from observations of the early Universe, in particular from the Cosmic Microwave Background (CMB), and in such a way researchers can stress-test the current standard cosmological model. Generally Prat Marti is also interested in developing methods and tools that enable researchers to robustly extract as much information as they can from upcoming galaxy surveys.