Abstract: During the last decades, galaxy sizes have been a very active research topic in Astrophysics given the fact that they are one of the few direct observables from objects in the distant Universe. In this seminar, I will review the different approaches that were traditionally taken, showing what we have learned about how our Universe evolves over time. However, galaxies are fuzzy objects, and as such a longstanding problem in galaxy evolution is the lack of a non-arbitrary galaxy size indicator. Low Surface Brightness (LSB) studies come to our rescue, as they show that galaxy disks have sudden drops in their surface brightness profiles, dubbed as galaxy truncations, that represent the limit of the radial location of the gas density threshold for star formation (i.e. true galaxy edges!). We compiled ultradeep HST observations of 1048 massive (M_stellar > 10^10 M_Sun) disks to obtain the size evolution for disk galaxies at 0 < z < 1 (Buitrago et al. in press), also extending our efforts by utilizing Machine Learning algorithms (Fernández-Iglesias et al. in press, Vega-Ferrero et al. in prep.). Milky Way analogs increase their sizes by a factor of two since z = 1, while at the same time decreasing their stellar surface mass density at the truncation position by an order of magnitude. The size evolution using these galaxy edges/truncations is more pronounced than in the effective radius case, with a factor of two better scatter in the mass-size relation, following a power law of (1+z)^-1. This fact is more in line with the evolution of the size of disk galaxies based on theoretical expectations, as effective radii are driven by light concentration, and thus promotes the role of our promising size proxy for better trace galaxy mass --both baryonic and dark matter-- assembly.