31st International Conference on Massive Storage Systems and Technology (MSST 2015) Sponsored by Santa Clara University, School of Engineering Since the conference was founded by the leading national laboratories, MSST has been a venue for massive-scale storage architects, operators, researchers, and vendors to discuss building and securing the world's largest storage systems for high-performance computing, web-scale systems, and enterprises.

May 30th — June 5th 2015 Santa Clara University Santa Clara California

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The field of Machine Learning is currently undergoing a significant transformation. From a niche methodology comprehensible to experts, it is becoming the main stream tool available for masses. From modeling thousands of data instances, it now needs to make sense of billions. From extending sophisticated intractable models, it now has to focus on parallelizing conceptually simple optimization procedures. From prototyping in Matlab, Machine Learning practitioners are now moving to programming GPUs and FPGAs—but they still use generic storage. In this talk, I will outline requirements to designing the smart storage systems of the future—to build the foundation for the next-generation intelligent data processing.

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Dr. Ron Bekkerman is an Assistant Professor of Data Science at the University of Haifa, Israel, and the CTO of a stealth mode startup. Before becoming an academic in 2013, Ron was the Chief Data Officer of Carmel Ventures, a leading Israeli VC fund. Prior to that, Ron was a Senior Research Scientist at LinkedIn, and a Research Scientist at HP Labs in the Bay Area. Ron holds a PhD in Machine Learning from UMass Amherst, and MSc/BSc in CS from the Technion. Ron serves on the Organizing Committee of SIGKDD, the top-tier Data Mining conference. He is the corresponding editor of "Scaling up Machine Learning", and the creator of a series of popular Machine Learning lectures on YouTube.

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Page Updated January 12, 2024