Prof. Dr. Emmanuel Müller

Big Data Analytics

Our research addresses theoretic challenges in correlation analysis, (un-)supervised feature selection, cluster and outlier detection as well as practical challenges in efficient computation of these models in large and complex data. The development of novel techniques for heterogeneous data spaces is a particular challenge in this area. We overcome the information loss of traditional techniques on homogeneous data sources and utilize the huge potential that is still unused in heterogeneous databases. Our group investigates algorithms for the selection of relevant attributes in high dimensional data, correlations in multivariate data streams, and homophile structures in attributed graphs.

Exploratory Methods

Our research aims at an easy to understand representation of data analytics results. We represent intrinsic dependencies between different information sources for human users. This includes exploring the automatic extraction of dependencies and pattern descriptions. This is an important research contribution for many applications where patterns have to be verified by the users. Human users require such descriptions of potential reasons for each of the detected patterns. This includes rule-based descriptions for unexpected patterns, semi-automated data exploration, and schema extraction.

Interdisciplinary Methods

We have observed in very many projects with both geo-scientists and industrial partners that application of state-of-the-art data mining methods is the first and important step for interdisciplinary research; however, it is not sufficient for long-term development. Hence, for our research group we aim at a joint research and development of methods together with domain experts in science and industry, as well as a deep understanding of respective methods on both sides. With such interdisciplinary research we achieve successful and sustainable innovations with other scientific disciplines and industrial partners.

Research Topics of Interest:

Broad Variety of Data Sources:

Broad Variety of Methods: