Developing analytical tools to address real world problems

The volume and variety of data available is constantly increasing. Hence, they provide a large potential to answer a range of questions. To understand these data and to model relationships emerging from them in order to derive answers, we need analytical tools. Dr. Benedikt Gräler and his team develop data-driven solutions to real world problems.

Exploring and researching analytical tools from linear statistics, recent multivariate distributions to modern machine learning (ML) and artificial intelligence (AI) approaches from the field of data science, the lab develops an appropriate solution for the problem at hand given the data available. A prerequisite is a solid data and business understanding. We use and contribute to open source tools where possible and encourage Citizen Science.

The lab addresses different R&D and PS projects covering a range of topics. The challenge of making Earth Observation time series accessible and providing unified processing and analysis tools has been and remains an engineering topic solving several open questions. The meaningful integration of heterogeneous data sources (from geospatial observations to official statistics) and adopting ML and AI algorithms to the special characteristics of spatial and spatio-temporal data are central themes of forthcoming tasks.