SEMINÁRIO DO DEPARTAMENTO DE ASTRONOMIA
The use of machine learning for the classification of the nuclear emission of galaxies
a talk by Roberto Bertoldo Menezes (Instituto Mauá de Tecnologia, Brasil)
Abstract:
One of the most relevant sub-areas of Extragalactic Astrophysics involves the study of the nuclear emission of galaxies, as it can provide important insights about their formation and evolution. Usually, this analysis is performed, with spectroscopic parameters, using diagnostic diagrams. This method, however, has its disadvantages and can lead, under certain circumstances, to imprecise classifications. In this talk, I will present a machine learning-based methodology to classify the nuclear emission of galaxies in H II regions, Seyferts and Low Ionization Nuclear Emission-Line Regions (LINERs), using photometric parameters. The methodology achieved accuracies of nearly 95% and may represent a significant contribution for studies in this area.
Short-Bio:
Dr. Roberto Bertoldo Menezes holds a Bachelor’s degree in Physics from Instituto de Física, Universidade de São Paulo (2006), a Master’s degree (2009), and a Ph.D. (2012) in Astrophysics from Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo. He conducted postdoctoral research in Astrophysics at the same institute (2012–2017) and at the Centro de Ciências Naturais e Humanas, Universidade Federal do ABC (2018). His research focuses on Extragalactic Astrophysics and Active Galactic Nuclei. He has published 35 articles in international journals, 13 of which as first author.
Google Meet: https://meet.google.com/pcw-gmem-jyi
Link da transmissão: https://www.youtube.com/c/AstronomiaIAGUSP/live