Big Data Computing

Our Goal

Our objectives can be divided into 3 main categories: a) scientific, b) educational and c) technological. Our mission can be summarized into the following statements:

  1. the TC and its activities will focus on basic research in the field of unconventional and traditional Big data processing and computation,
  2. the TC will actively support the dissemination of Big data know-how amongst the scientific community and especially the activities of young researchers,
  3. the TC will support the transfer of latest research results from the area of Big data to industry.

Big data, its high-quality processing and analysis (especially nontraditional), is vitally important for today's society. The aim of this technical committee is to establish a community of active Big data processing, analysis, computation, and application experts build around internationally recognized scholars active in academia and senior engineering experts from various engineering fields.

Join Us

Join us to establish the new interdisciplinary fusion of the fields of Big data and unconventional methods of computation. It is clear that by this "fusion", one can expect an emergence of new results and methods leading to important applications in many branches of science and technology dealing with Big data.

We support the study of state-of-the-art strategies and schemes of mutual fusion of the aforementioned methods and research fields with a special focus on knowledge sharing and community building to facilitate deeper understanding of these complex problems. More importantly, we pay special attention to new, original, and interesting technologies, developed for Big data and it's processing, which may prove game-changing in our everyday lives and in our society as a whole.

One of the most important goals of this technical committee is to provide an international forum for the exchange of ideas and ground-breaking results among the global community of Big data researchers. We emphasize the use of novel and unconventional methods and strongly support young researchers and the new generation of scientific experts interested in Big data theory and applications. We also try to broaden the bridge to emerging technologies and potential applications, making Big data processing more practical and useful.