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SUMMARY:EESS talk on "Big data analytics for extracting mobility patterns"
DTSTART:20221108T121500
DTEND:20221108T131500
DTSTAMP:20260406T203417Z
UID:4b876fc10b4063a00613fffdb2892993dd2b3cfd37d873fb6efddce5
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Christophe Claramunt\, Professor\, ISblue (Interdisciplinar
 y School for the Blue Planet)\, France\, visiting professor at LASIG\nAbst
 ract:\nThe advent of information and communication technology\, the Intern
 et of Things and social medias have led our society toward a digital era t
 hat offer new opportunities for the understanding of urban and environment
 al systems. The proliferation of personal computers\, smartphones\, intell
 igent autonomous sensors\, and pervasive network interactions with individ
 uals offer novel avenues for the understanding of human activities that ha
 ppen in space and time. This seminar will introduce a series of methodolog
 ical and practical advances and contributions of this digital revolution t
 o the understanding of mobility patterns in urban and regional environment
 s. I will also discuss with the audience a few key implications of this pa
 radigm shift and some of the upcoming research challenges.\n\nShort biogra
 phy:\nChristophe Claramunt is a professor of computer science and deputy d
 irector of the Interdisciplinary School for the Blue Planet (www.isblue.fr
 ) whose mission is to advance marine science\, marine technology and ocean
  innovation. He started his academic career as a senior researcher at EPFL
  in the rural engineering department then moved to the Nottingham Trent Un
 iversity before chairing the French Naval Academy Research Institute. He i
 s currently back at EPFL as a visiting research fellow at the LASIG. His r
 esearch focuses on theoretical and multidisciplinary aspects of geographic
 al information science and their applications to urban\, maritime and envi
 ronmental systems. Over the past few years\, he has been particularly work
 ing on the many opportunities offered by the digital revolution\, big data
  and sensor-based technology to urban and environmental sciences.
LOCATION:GC B1 10 https://plan.epfl.ch/?room==GC%20B1%2010 https://epfl.zo
 om.us/j/63802032408
STATUS:CONFIRMED
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