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2016 New York Scientific Data Summit (NYSDS)
August 14, 2016 @ 8:00 am - August 17, 2016 @ 5:00 pm
The 2016 New York Scientific Data Summit (NYSDS) will be held on August 14-17, 2016 at New York University.
The New York Scientific Data Summit (NYSDS) aims to accelerate data-driven discovery and innovation by bringing together researchers, developers and end-users from academia, industry, utilities and state and federal governments. With keynote speakers from industry and international big-science projects, the 2-1/2 day conference is organized into five sessions with topics including streaming data analysis, long term data storage, curation, and sharing, experimental data, industry solutions and challenges for big data and the convergence of data and HPC.
Keynote speakers Incl.:
· Scott Klasky, ORNL, Everything you ever wanted to know about Scientific Exascale Data.
· John Wu, LBNL, Searching Workflow Documentation with MPO
· Leslie Greengard, Simons Foundations for Data Analysis, Fast Algorithms for Inverse Problems in Acoustic Scattering and Cryo-electron microscopy
· Ryan Quick, PayPal, Leveraging “Right Now”: Concepts, Challenges, and Directions for Analytics on the Wire
· Salman Habib, ANL, High Performance Computing for Data-Intensive Tasks: Friend or Foe?
Please register soon as participation is limited to 150 attendees only.
Jointly organized by Brookhaven National Laboratory (BNL), Stony Brook University (SBU), New York University (NYU) and the IEEE Computer Society Long Island Chapter NYSDS 2016 will take place at NYU Kimmel Center for University Life, 60 Washington Square South, New York, NY 10012 USA. In 2016 for the first time the conference will publish conference proceedings through IEEE. Sponsors include BNL, the Institute for Advanced Computational Science at SBU, the NYSTAR High-Performance Computing Consortium (HPC2), New York University Center for Data Science, the Moore-Sloan Data Science Environment and the IEEE Computer Society Long Island Chapter.
For more information contact conference coordinator: