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Ian Foster

Keynote

 

Learning Systems for Science

Ian Foster
Argonne National Laboratory and the University of Chicago, USA

 

Abstract

New learning technologies seem likely to transform much of science, as they are already doing for many areas of industry and society. We can expect these technologies to be used, for example, to obtain new insights from massive scientific data and to automate research processes. However, success in such endeavors will require new learning systems: scientific computing platforms, methods, and software that enable the large-scale application of learning technologies. These systems will need to enable learning from extremely large quantities of data; the management of large and complex data, models, and workflows; and the delivery of learning capabilities to many thousands of scientists. In this talk, I review these challenges and opportunities and describe systems that my colleagues and I are developing to enable the application of learning throughout the research process, from data acquisition to analysis.

Slides

Wednesday 13th February 2019  2:10 pm – 2:50 pm – Schedule

 

 

 

 

Ian Foster
Director, Data Science and Learning Division; Senior Scientist; Distinguished Fellow, Argonne National Laboratory
Arthur Holly Compton Distinguished Service Professor of Computer Science, University of Chicago
Fellow, Institute for Molecular Engineering
Chief Troublemaker, Globus, www.globus.org
Author: Cloud Computing for Science and Engineering https://cloud4scieng.org

Wikipedia

IanFoster.org

 

awm_010385-01

Panel at Multicore World 2013 – Nicolás Erdödy (Open Parallel – Moderator) – Paul McKenney (IBM) – Ian Foster (Argonne) – Poul-Henning Kamp (FreeBSD) – Mark Moir (Oracle Labs)

 

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