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Artificial Intelligence for Science, Industry and Society

AISIS2019
21-25 October, 2019
Universidad Nacional Autónoma de México, Mexico City, México
The recent progress in Artificial Intelligence and Machine Learning has provided new ways to process large data sets. The new techniques are particularly powerful when dealing with unstructured data or data with complex, non-linear relationships, which are hard to model and analyse with traditional, statistical tools. This has triggered a flurry of activities both in industry and science, developing methods to tackle problems which used to be impossible or extremely hard to deal with.
 
Due to this situation, we are proposing to organise a meeting where the following key elements would be covered:
The meeting is oriented towards scientists and educators as well as industry and policy makers in R&D.
 
Editorial Board
 
Boris Escalante , CViCom-UNAM
Federico Carminati , CERN
Gergely Barnafoldi , Wigner RCP Hungarian Academy of Sciences (HU)
Guy Paic , ICN-UNAM
Lukas Nellen , ICN-UNAM
Rafael Mayo , CIEMAT
Steven Schramm , University of Geneva
Zeljko Ivezic , University of Washington
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