Research - Page 2With the advancement of modern technology also many new problems arise. For example, the enormous potential capabilities of a future computer and its practical needs require the discovery of ways parallelism can be used effieciently. Sometimes this seems very difficult or even impossible. The most popular example illustrating this is that nine women cannot give birth to a child within one month.
There is also a huge need for (more) intelligent computer. In this regard, the list of desiderata is long ranging from natural language support to learning.
Furthermore, during the last two decades we are faced with an enormous growth of the data that are electronically available. The quantity of supplied data doubles itself about every 20 months. Examples are mapping the entire human genome, astronomical data collected by satellites, business data of large companies, and semi-structured data in the World Wide Web. But just having or collecting data is not enough. We aim to extract the knowledge contained in the data. But this is easier said than done. The quantity of the data to be analyzed is enormous (GIGABYTE area). The data can be present in very inhomogeneous formats. The data are frequently incomplete and noisy (e.g. measuring errors). The task is not to retrieve individual data but to discover knowledge, i.e. the regularities hidden in the data.
Our laboratory addresses several of these questions. In particular, our research interests comprise but are not limited to:
This page is updated whenever new information is available.
Last update October 10, 2016.