DFG funds AI Research Unit
As part of the funding initiative in the field of artificial intelligence (AI), the Deutsche Forschungsgemeinschaft (German Research Foundation, DFG) is funding the new joint Research Unit "DeSBi" of Humboldt-Universität zu Berlin, Hasso Plattner Institute (HPI), University of Potsdam (UP), Charité - Universitätsmedizin Berlin, Max Delbrück Center for Molecular Medicine and Fraunhofer Heinrich Hertz Institute, which aims to use AI technologies to provide biomedical scientists with better methods for gaining knowledge from structured data in the future. Our School member Sonja Greven will be the spokesperson of the Research Unit.
In the Research Unit, experts from the fields of machine learning and statistics will collaborate to improve interpretability, uncertainty quantification, and statistical inference for deep learning, and to improve the modeling flexibility of statistical methods for structured data. In particular, methods will be developed to enable statistical inference for structured data through uncertainty quantification, hypothesis testing, and adjustment for confounding variables, and to improve explanations of structured data through hybrid statistical and deep learning models, population- and distribution-level explanations, and robust sparse explanations. There will be a feedback loop between method development and biomedical applications as they collect structured data such as images, gene sequences, or panel data and require quantification of uncertainty, adjustment for confounding variables, and testing of hypotheses with statistical error control in addition to good predictions. Moreover, the developed methods will be applicable in many fields.