IEEE Symposium on Computational Intelligence in Big Data

IEEE CIBD’2015 will be held simultaneously with other symposia and workshops in one location at the 2015 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2015).

This international event promotes all aspects of the theory and applications of computational intelligence. Sponsored by the IEEE Computational Intelligence Society, this event will attract top scientists, researchers, professionals, practitioners and students from around the world. The registration to SSCI 2015 will allow participants to attend all the symposia, including the complete set of the proceedings of all the meetings, coffee breaks, lunches, and the banquet.

Scope and Topics

IEEE CIBD’2015 will bring together scientists, engineers, researchers and students from around the world to present recent advances, explore challenges and opportunities in the application of Computational Intelligence (CI) techniques to the emerging and exciting field of Big Data and data sciences. This conference will provide a forum to present recent results in CI algorithms, software and systems for big data analytics, discuss the practical and theoretical challenges in big data, and explore CI solutions to tackle these challenges and issues.

IEEE CIBD’2015 solicits papers that report new research results that apply CI technologies, such as deep learning, neural networks and learning algorithms, fuzzy systems, evolutionary computation, and other emerging techniques to Big Data, ranging from theory, methodologies and algorithms for handling the 3Vs (Volume, Variety, and Velocity) of big data, to their applications to the development of big data analytics systems. Successful applications of big data in industries are also encouraged to participate in this event.

Topics of IEEE CIBD’2015 include but are not limited to:

  • Integrative analytics of diverse data resources
  • Integration of structured and unstructured data
  • Deep learning of big data
  • Big data in healthcare
  • Big data in industrial internet of things
  • Big data in future media
  • Big data in finance and economy
  • Big data in public services
  • Big data in social media
  • Big data in intelligent robotics
  • Big data driven new business
  • Extracting understanding from distributed, diverse and large-scale data resources
  • Extracting understanding from real-time large-scale data streams
  • Predictive analytics and in-memory analytics
  • New information infrastructure for big data
  • Big data visualization and visual data analytics
  • Semantic technologies for big data
  • Scalable learning techniques for big data
  • Optimization of complex systems involving big data
  • Data governance and management in big data
  • Human-computer interaction and collaboration in big data
  • Big data and cloud computing
  • Applications of big data, such as industrial processes , business intelligence, healthcare, bioinformatics and security

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