Speaker
Description
Astronomers and astrophysicists use more and more on Big Data from large sky surveys and simulations. It is thus inevitable that machine learning found its way into the process of exploitation of
these huge data sets. In the first part I'll review some recent applications of machine learning in
astronomy. The topics cover galaxy classification, asteroseismology, discovery and
characterization of exoplanets, just to name a few. In the second half of this talk I'll present
my Lendület group's work on classification of variable stars and astrophysical transients which is
part of the Hungarian in-kind contribution offered in exchange of involvement in and data access to
one of the most important ground-based astronomical projects of the next decade, the US and Chilean
led Vera C. Rubin Observatory's Legacy Survey of Space and Time.
