International Collaboration
International Research Center of Big Data Science and Engineering
Release time:November 30, 2017

Founded in September 2012, the International Research Center of Big Data Science and Engineering is an important part of the International Research Institute for Multidisciplinary Science. It is jointly set up by Beihang University, University of Edinburgh, University of Leeds, Hong Kong University of Science and Technology, University of Pennsylvania, Arizona State University, and University of Ottawa. The center takes the advantage of the information technology in the era of Internet and big data to integrate resources of advanced research, education and enterprises in this field, establishing itself as an academic highland of big data science and engineering. As a productive international scientific cooperation center, it is playing a leading role in scientific research, industry standard setting and talent cultivation.

The center is scientific research task-oriented, realizing the crossing and blending of different disciplines. It implements a system wherein the director shall assume overall responsibility, as well as the scheme of academic committee review. It has set up an international academic committee to guide the research activities, review its research projects and direction, and provide advice and consultive support for its strategic planning. The committee consists of international famous scientists in the related fields, and its plenary meeting is held every two years. Also, the center has set up a scientific steering committee, which is mainly responsible for the coordination between research departments and project teams, such as the crossover and collaboration between different research directions, and the setting of new directions.

The center covers a wide variety of research topics, including the basic theory of big data science and engineering, big data-oriented Internet software theory and technology, distributed computing theory and technology for big data, big data model theory and storage methods, big data security and privacy protection technology, the basic theory and technology of big data quality management, and domain-oriented big data engineering.