ExaHealth 2021: Exascale computing and machine learning for public health

Europe/Zurich
Virtual / CERN

Virtual / CERN

Virtually everywhere
James Beacham (Duke University (US))
Description

            

With the advanced state of high-performance computing (HPC) at the exascale and the continued development and proliferation of machine learning (ML) / deep learning techniques in all sectors, it is imperative that we ensure these resources are being used not only for commercial applications but in a realm that affects us all: Public health.

Projects supported by the European Union (such as Exscalate4COV and LIGATE, with the participation of dozens of institutions, including Chelonia Applied Science, hosted at the Innovation Office of University of Basel) as well as initiatives pioneered by CERN openlab (such as CERN Science 4 Open Data) demonstrate the possibilities and prospects of leveraging exascale HPC and ML in the health sciences. But what are we missing? How can we ensure that we will respond quickly and efficiently to future health situations, including (but not limited to) pandemics?

Join us at ExaHealth 2021 to explore how exascale computing and ML are used in the health and life sciences and to begin charting a course for the future.

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Remote connection details will be provided to registrants on the day of the event. Please register to ensure you can connect!