Sotiria Fotopoulou

Astrophysicist. Data enthusiast.

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Data-Intensive AstroNomical Analysis [D.I.AN.A.]

I lead the D.I.AN.A group at the University of Bristol, and I co-lead the AGN Work Package in Euclid.

We use large multiwavelength datasets to understand the impact of supermassive black holes in the evolution of galaxies. We develop automated methods for creating high-fidelity multiwavelength datasets, harness machine-learning methods for object classification & physical parameter estimation, and explore the impact of AGN in galaxy evolution through the statistical analysis of large datasets.

Use the links below to learn more.

Public Codes

ADS-megalib [GitHub]

Merge all of your NASA/ADS libraries into one!

• Export a combination of stored libraries into a single .bib file

• Create merged libraries on your ads account

Star - Galaxy - QSO classification [GitHub]

Unsupervised machine-learning classification - application of HDBSCAN

• classify sources using photometry

• method presented in Logan & Fotopoulou 2020

Astro-PostgreSQL Docker image [GitHub]

Run a PostgreSQL deamon through docker, including the pg_sphere and pg_healpix extensions.

• pg_sphere provides astronomy related definitions such as points, coordinates, etc

• pg_healpix provides access to tessellation ID of sky coordinates.

AstronomicAL [GitHub]

An interactive dashboard for visualisation, integration and classification of data using Active Learning presented in Stevens et al., 2021

INSPEC-Z [GitHub]

Interactive visualisation and verification of 1D spectra with matplotlib.

• Convenience functionality for managing large surveys, e.g. filtering, flag homogenisation

• Simple conda installation and docker image (only for Mac OS)