AGN Science in the Era of Big Data: From DESI to the AI Revolution

Speaker

Stéphanie Juneau | NSF NOIRLab, NSF-Simons CosmicAI

Abstract

As we advance deeper into the data-rich era, AGN and galaxy co-evolution studies are entering a vast discovery space fueled by massive multi-wavelength datasets, offering us powerful statistical leverage for population studies. With the Dark Energy Spectroscopic Instrument (DESI) already delivering unprecedented catalogs and upcoming surveys like Rubin LSST and Roman on the horizon, the challenge is shifting from data acquisition to advanced analysis techniques and astrophysical interpretation. In this talk, I will highlight recent breakthroughs from DESI, including the most extensive census of black holes in dwarf galaxies and the identification of rare, short-lived phases such as changing-look AGN and extreme broad-line quasars. I will also present recent work on mapping ionized gas to probe AGN feedback with the James Webb Space Telescope (JWST), demonstrating how this approach provides a crucial high-redshift complement to current surveys. Lastly, I will discuss how the integration of multi-wavelength datasets and Machine Learning/AI is redefining AGN identification and guiding our vision to address long-standing questions about black hole/galaxy co-evolution.

Connection information:

https://science.nasa.gov/astrophysics/programs/cosmic-origins/community/agn-sig-vision-series-26-may-2026/ (Zoom Registration required)