DFG to establish 4 new research units
The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) has approved the establishment of four new Research Units. This decision was taken by the DFG's Senate at its February meeting in Bonn. The purpose of the research consortia is to offer researchers the opportunity to devote their time to topical questions in their disciplines and to establish innovative research directions.
As with all DFG Research Units, the new groups will collaborate across locations and disciplines. Their main topics are computer-aided knowledge representation, the structure and dynamics of ecological networks, new statistical procedures, and nano innovations for optoelectronics.
During the initial three-year funding period, the new Research Units will receive approximately 6.8 million euros. The DFG now funds a total of 199 Research Units.
The new units are as follows (in alphabetical order by coordinating university):
A key research topic in the field of artificial intelligence is knowledge representation and inference, the computer-aided drawing of conclusions from bodies of knowledge. Until now, qualitative approaches have dominated this field. The aim of the "Hybrid Reasoning for Intelligent Systems" unit (HYBRIS for short) is to combine qualitative and quantitative forms of drawing conclusions in new ways. These will be linked with overarching issues of logic-based knowledge representation, which will be investigated jointly and with regard to their potential use by theoreticians and experts from robotics and bioinformatics. (Coordinating University: RWTH Aachen, Prof. Dr. Gerhard Lakemeyer)
"Networks on Networks: The Interplay of Structure and Dynamics in Spatial Ecological Networks" is the focus of a new Research Unit which unites researchers from the fields of physics and biology. The group will study the example of the extensive marine feeding networks. In doing so, the researchers will examine how local networks interact with networks in other habitats with respect to their scope and structure, their biodiversity and their population dynamics. In addition to collecting and analysing empirical data, the researchers will use statistical methods to simulate linked networks. In sum, the dynamics of communities, as well as the "laws of movement" which govern species, will be examined and applied to our understanding of ecosystems (and their protection). (Coordinating University: Technische Universität (TU) Darmstadt, Prof. Dr. Barbara Drossel)
In light of rapidly increasing data volumes – not only in science – modern statistical processes are becoming ever more significant. The Research Unit "Structural Inference in Statistics: Adaption and Efficiency" aims to use innovative mathematical and numerical approaches and methods to develop new, high-performance processes which utilise the structural properties of the complex, high-dimensional data on which they are based. The long-term goal of the initiative, which is being pursued jointly by statisticians from Berlin, Hamburg and Potsdam, is to develop a general concept which enables automatic and simultaneous alignment with the various structures existing in the data. The issue will be examined from both a basic research and an applied perspective. (Coordinating University: Humboldt University of Berlin, Prof. Dr. Markus Reiß)
An important research field in nanotechnology is the creation and investigation of semiconductor nanowires. These provide great potential for future applications in electronic and optoelectronic modules. Exploring these opportunities experimentally and theoretically is the focus of the "Dynamics and Interactions of Semiconductor Nanowires for Optoelectronics" Research Unit. In doing so, the researchers aim to investigate the interaction between nanowires and their environment and the targeted functionalisation of the nanowires. This research promises groundbreaking insights into the physical and chemical properties of nanowires and their applications in optoelectronics. (Coordinating University: Friedrich Schiller University of Jena, Prof. Dr. Carsten Ronning)
Provided by Deutsche Forschungsgemeinschaft