Research Centers of the German UDS
The scientific exchange and collaboration between the professors and scientists at the German University of Digital Science is organized in Research Centers, which are agile and temporary organizational units that provide an inspiring framework for the dynamic research activities of the researchers. Here, professors, research associates, postdocs and PhD students work together on their research projects and dissertations. Each Research Centre has its own PhD program, known as a Research School. The joint supervision of doctoral candidates by professors ensures an open and broad perspective from the outset when working on the research topic agreed with the doctoral supervisor.
Research Center for Learning Analytics and Digital Education
Speaker: Prof. Dr. Christoph Meinel
Learning analytics refers to collecting, aggregating, analyzing and evaluating data about learners and their digitally supported learning contexts. This form of data analysis is motivated by technical, pedagogical, political and economic considerations. Evaluating learner data makes it possible to assess the effectiveness of digital learning formats and methods in order to better understand and optimize the overall learning process. Digital education enables personalised support for learners. The German University of Digital Science can use this directly to improve its services.
Research Center for Digital Science
Speaker: Prof. Dr. Mike Friedrichsen
Digital science should take into account all aspects mentioned in the concepts of e-Science, e-Infrastructures, Open Science and Science 2.0 as issues to be considered in policy making. The different terms refer to the development of new ways of conducting scientific activities using ICT, incorporating previous themes and adding a new layer. Digital science is the new growth of science and research resulting from all the existing and new, constantly evolving possibilities offered by communication networks, the digital availability of scientific content and new activities and interactions enabled by technology.
Research Center for Artificial Intelligence
Speaker: Prof. Dr. Raul Rojas
Artificial intelligence has gone from being an exotic subject of research to a driving force in the development of IT applications over the past 30 years. The focus of research is on what is known as machine learning, i.e., the computer is supposed to discover the solution strategy for a wide variety of problems from large amounts of data on its own. This is why today’s AI is developing hand-in-hand with strategies for storing and making available massive amounts of data. Today, this is known as big data, i.e., data that is no longer collected locally, but in the cloud around the world. Deep learning is therefore much more than the use of multi-layer neural networks. Deep learning requires combining all of the above to create adaptive systems that can understand and translate language, or even drive autonomous vehicles.