Monthly Archives: November 2013
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NOTE: For all attendees that have registered to the full conference (including workshop) or workshop only, you will receive an invitation for an account for the DiscoverText software that will be used during the workshop. Please download the software before the workshop. If there are any questions on this software, please direct them to Stuart Shulman [email protected].
Keynote Speakers announced:
Zhen Liu, Microsoft, China
Chunming Hu, Beihang University, China
Wayne Huang, Ohio State University, USA
Guanling Chen, University of Massachusetts at Lowell, USA
Mu Li, Baidu, China
Alvin Chin, Microsoft, China
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The Third ASE International Conference on Big Data Science and Computing aims to bring together academic scientists, researchers and scholars to exchange and share their experiences and research results in Advancing Big Data Science & Engineering (BIGDATA). The phrase “big data” in this solicitation refers to large, diverse, complex, longitudinal, and/or distributed data sets generated from instruments, sensors, Internet transactions, email, video, click streams, and/or all other digital sources available today and in the future.
The current focus is to advance the core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets so as to: accelerate the progress of scientific discovery and innovation; lead to new fields of inquiry that would not otherwise be possible; encourage the development of new data analytic tools and algorithms; facilitate scalable, accessible, and sustainable data infrastructure; increase understanding of human and social processes and interactions; and promote economic growth and improved health and quality of life. The new knowledge, tools, practices, and infrastructures produced will enable breakthrough discoveries and innovation in science, engineering, medicine, commerce, education, and national security.
A long-term strategy to address various big data challenges, which include advances in core techniques and technologies; big data infrastructure projects in various science, biomedical research, health and engineering communities; education and workforce development; and a comprehensive integrative program to support collaborations of multi-disciplinary teams and communities to make advances in the complex grand challenge science, biomedical research, and engineering problems of a computational- and data-intensive world.
