The advent of the digital information age has led to an inevitably increasing growth of heterogeneous data. Caused by the rapid spread of internet-enabled modern devices and their powerful processing capabilities as well as advanced means of data communication, users and systems are able to generate, process, and share data in a massive scale. Concomitant with the resulting multitude and versatility of data made available in scientific and non-scientific domains, today’s data management and analysis algorithms are supposed to adapt to various notions of similarity and different data types in order to dynamically analyze large-scale databases and streams efficiently with respect to diverse information needs.
Digitizing data and algorithmizing their inherent characteristics are among the great challenges in computer science. We are focusing our research on methods and techniques for efficient and scalable data management and analytics. To this end, we are developing and investigating concepts, models, and algorithms for processing, managing, indexing, querying, and analyzing data from various domains. Our aim is not only to investigate and advance state-of-the-art approaches, but also to gain new insights into the specific fundamental methods and to generalize our findings for further cross-domain research in the areas of Data Engineering, Big Data, Data Mining, Machine Learning, and Data Science.
A list of our research projects can be found below. More information about these projects can be found here.
- Applied IoT Data Analytics (since 2017)
- Query Processing (since 2014)
- Metric and Ptolemaic Access Methods (since 2011)
- Similarity Search (since 2011)
- Medical Video Analysis (2015 - 2018)
- Video Search and Retrieval (2015 - 2018)
- Gesture Analytics (2014 - 2018)
- Sequential Pattern Mining (2014 - 2015)
- Semantic Data Access (2013 - 2016)
- Performance Studies (2010 - 2015)
- Signature Quadratic Form Distance (2009 - 2013)
- Multimedia Data Exploration (2008 - 2012)
A list of publications can be found here. Please contact us for further information about our research topics.