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SUMMARY:From theory to practice: how Python enabled modern astronomical da
 ta analysis - Emille Ishida
DTSTART;TZID=Poland:20260720T101000
DTEND;TZID=Poland:20260720T111000
DTSTAMP:20260907T160815Z
UID:pretalx-euroscipy-2026-8DKJ7N@pretalx.com
DESCRIPTION:The intrinsic difficulties related to gathering and processing
  astronomical data have traditionally branded it a “data starving” fie
 ld. The situation changed only in the last few decades with the advent of 
 large scale sky surveys that made publicly available the first extremely l
 arge and coherent astronomical data sets. In this context\, Python has pla
 yed a crucial role in enabling an extremely fast development of tools amon
 g the astronomical community\, thus fostering an unprecedented revolution 
 on how experts interact with their data. In this talk\, I will describe th
 e first stages of astronomical data analysis\, how new data challenges wer
 e imposed in the last century and how Python was crucial to change the par
 adigm of astronomical data analysis. Finally\, I will discuss the new fram
 ework of astronomical data and the impact of python developed tools in the
  process of scientific analysis. Finally\, I will highlight the most chall
 enging issues still to be faced in the era of the surveys like the Vera C.
  Rubin Observatory\, as well as the impact of foundation models in the sci
 entific exercise of astronomical discovery.
LOCATION:Room 1.38 (Ground Floor\, Turing)
URL:https://pretalx.com/euroscipy-2026/talk/8DKJ7N/
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