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2018 International Materials Research Society Me ... (No replies)
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Dear Colleagues,
The advent of big data analytics in the computing science community along with the reduction in computing and memory costs over the last few years have brought powerful machine learning techniques to the forefront; such methods are now routinely used in business, transactional, and social media applications. These machine learning methods hold tremendous promise to advance various facets of nanoscale materials research, particularly via successfully combining them with first-principles physics, atomistic simulations, and experimental characterization. This symposium aims to facilitate and strengthen the synergistic approach to experimental and theoretical works of experts academia, national labs, and industries. Researchers will discuss the latest developments in machine learning tools and techniques to enable accelerated discovery, characterization and design of hybrid materials and novel device architectures for a range of different emerging energy applications and technologies.