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

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