Collective Learning Data Lab

Data fuels the digital economy. This demands training new generations of experts on how data is collected, stored, processed, and analyzed. Corvinus University of Budapest (CUB) is working to become a leading business and economics university in Central and Eastern Europe by combining data science skills with expert knowledge in business and economics. The support of the ERA Chair Program will reinforce institutional reforms at CUB designed to transform it into a hub of research and teaching excellence in applied data science, expanding the international attractiveness of CUB through cutting-edge training programs and innovative industry collaborations. We will establish the new Collective Learning Data Lab (CLDL) with the leadership of Professor Csar Hidalgo, a world-class researcher in data science, economic geography, and network science. By leveraging synergies with outstanding research groups at CUB, the Collective Learning Data Lab is projected to grow into a leading Center for Data and Network Science. This will create an environment for the university to learn key methods and publish in top interdisciplinary, economics, business, and social science journals. The Lab will be a flagship project involving students in experiential data-driven work. Lab members will engage in advising PhD programs and in developing BA specializations and Master programs in social- and business-oriented data science. The Lab will widen CUBs industry collaborations with data-oriented companies and public policy use cases. Building on Budapests strong tradition in network science, CLDL will impact Hungary and Central and Eastern Europe by equipping society with the skills needed to undertake new challenges.