Two million in state funding for the new "Datencampus" (Data Campus) research project at Kiel University
Boost the use of artificial intelligence (AI) across all research disciplines. Promote the sustainable digitalisation of science in Schleswig-Holstein. Use the latest discoveries from computer science to address current social and economic questions in a targeted manner. These are the goals of the new "KI@CAU Datencampus Kiel" research project at Kiel University (CAU). The project will receive around two million Euros from the state of Schleswig-Holstein for this purpose and is to run for three years. Today (Thursday 24 March), Dirk Schröder, head of the State Chancellery, handed over the funding approval notice to the Kiel project team.
"With the Datencampus, we are pooling knowledge, methods and competencies related to data and AI for the university location of Kiel, thus taking knowledge and technology transfer to a new level," said Schröder: "Schleswig-Holstein already recognised the megatrends of AI and data science at an early stage. We are now achieving another important milestone so that we can continue to shape the megatrends in the future." In cooperation with Kiel University of Applied Sciences, a data and AI platform is being developed at the CAU which brings technology directly to where it can be applied in practice.
Impulses for the digital transformation
"Kiel University, just like science as a whole and all other areas of society, is in the midst of a digital transformation. In this important phase, projects such as the Datencampus are decisive catalysts for making the best possible use of digital potential for scientific progress," emphasised Vice-President Professor Eckhard Quandt. "This means that the Datencampus also acts as a driving force for innovations at the CAU, in the AI location of Schleswig-Holstein and beyond."
"To date, in computer science we often only work with sample data sets, while in the application disciplines, the latest methods of computer science are often not used for data processing," explained Professor Dirk Nowotka, who is responsible for the project at the CAU together with Professor Olaf Landsiedel, Professor Agnes Koschmider and Professor Matthias Renz. "The collaboration between the disciplines will enable completely new insights into large volumes of data. This will allow us to uncover new relationships in data that have remained hidden so far."
Artificial intelligence in partnerships
In order to launch interdisciplinary cooperation in the Datencampus, the four computer scientists will form four tandem initiatives with scientists from other disciplines. These will combine innovative methods of data processing with practical applications in research. Together, the tandem teams will develop and answer novel, interdisciplinary research questions.
The researchers are developing a virtual data and AI platform as the technical core. Here, the tandems will test modern data analysis and AI methods, and investigate their use in the research process of the respective disciplines.
The four tandems (together with their respective working groups) are:
- Professor Dirk Nowotka and Professor Marco Liserre, topic: Intelligent Battery Management Strategy based on Machine Learning Technology (Electrical Engineering)
- Professor Agnes Koschmider with Professor Michael Krawczak and Professor Sebastian Graf von Kielmannsegg, topic: Biobanks (Medicine/Big Data and Privacy)
- Professor Matthias Renz and PD Dr Tim Kerig, topic: Big Exchange (Computational Archaeology)
- Professor Olaf Landsiedel with Professor Kai Roßnagel, topic: Edge AI for Data Analytics in Free Electron Lasers (Physics)
"The tandem concept is applicable to all specialist fields," emphasised Nowotka. For example, he sees marine sciences as a potential area of application. Large-scale measurements and satellite-based monitoring provide huge volumes of data. These harbour enormous potential for designing ocean models to improve climate forecasts, for example, or for making the current effects of climate change even more tangible. Nowotka also sees further areas of application for AI methods in medicine, for example in biomedical imaging processes or in AI-supported diagnostics: "Here, as in many specialist areas, there is optimisation potential that we want to exploit by using the latest AI technology."
From theory to practice
Another element of the Datencampus is expansion into application-oriented research. This is where Kiel University of Applied Sciences (FH Kiel) comes into play, with its many years of experience in technology transfer to business. "The application orientation brings an extremely useful aspect to the Datencampus and rounds off the research cycle," said Professor Stephan Schneider, project leader at Kiel University of Applied Sciences. "The usefulness of an AI solution can only be determined once it is applied in practice. In this way, we can gain valuable insights into AI methods and models, which in turn can be incorporated into the research process."
The wide range of areas of application makes the Datencampus attractive and unique. Schneider added "Together with strong partners from business and administration, we want to identify potential applications of AI and data science, and support these with our research."