Abstract: Understanding physical processes responsible for the formation and evolution of galaxies like the Milky Way is a fundamental but unsolved problem in astrophysics. Most stars are long-lived, and using the stars as ​“fossil records” (what is known as galactic archaeology) can offer unparalleled insight into the assembly of galaxies. The landscape of galactic archaeology is rapidly changing thanks to ongoing large-scale surveys (astrometry, photometry, spectroscopy, and asteroseismology), which provide a few orders of magnitude more stars than before. I will discuss various ​“phenomenological” opportunities enabled by large surveys. I will also discuss how we could describe substructures in the Milky Way through the lens of deep learning.