Big Data Analytics (openHPI)
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Emmanuel Müller
Prof. Dr. Emmanuel Müller is head of the Knowledge Discovery and Data Mining research group, which has been established in cooperation with the German Research Centre for Geosciences (GFZ). Data Mining, as part of many scientific and industrial applications, does not end with the execution of algorithms. With data mining algorithms, resulting in discovery of unknown, novel, and unexpected patterns, one should aim at assisting humans in their daily decision making. On the one side, Professor Müller and his researchers investigate efficient algorithms, which scale with size and complexity of the data. And on the other side, algorithms generate verifiable knowledge for human users.
The group's research goals are such scalable and verifiable data mining methods for large and complex data. These include algorithms for the selection of relevant attributes in high dimensional data, correlation analysis in multivariate data streams, and homophile structures in attributed graphs. Furthermore, the group develops data mining algorithms for multi-scale sensor data and interactive exploration of heterogeneous information systems in cooperation with the GFZ.