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UID:pretalx-euroscipy-2026-8DKJ7N@pretalx.com
DTSTART;TZID=CET:20260720T101000
DTEND;TZID=CET:20260720T111000
DESCRIPTION:The intrinsic difficulties related to gathering and processing 
 astronomical data have traditionally branded it a “data starving” fiel
 d. The situation changed only in the last few decades with the advent of l
 arge scale sky surveys that made publicly available the first extremely la
 rge and coherent astronomical data sets. In this context\, Python has play
 ed a crucial role in enabling an extremely fast development of tools among
  the astronomical community\, thus fostering an unprecedented revolution o
 n how experts interact with their data. In this talk\, I will describe the
  first stages of astronomical data analysis\, how new data challenges were
  imposed in the last century and how Python was crucial to change the para
 digm of astronomical data analysis. Finally\, I will discuss the new frame
 work of astronomical data and the impact of python developed tools in the 
 process of scientific analysis. Finally\, I will highlight the most challe
 nging 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 scie
 ntific exercise of astronomical discovery.
DTSTAMP:20260603T195723Z
LOCATION:Room 1.38 (Ground Floor\, Turing)
SUMMARY:From theory to practice: how Python enabled modern astronomical dat
 a analysis - Emille Ishida
URL:https://pretalx.com/euroscipy-2026/talk/8DKJ7N/
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