Algorithms
The Algorithms cluster performs fundamental research on methods and techniques for algorithm design and analysis, with an emphasis on natural computing and data mining algorithms. We aim for application of our algorithms in medicine, bio- and chemoinformatics, engineering, and physics. The cluster is divided in three groups:
- Data Mining group
- Natural Computing group
- Theoretical Computer Science group
Data Mining
prof.dr. Joost N. Kok (head)
Data mining refers to the process of analyzing data in the hope of finding patterns that are novel, interesting, and useful. It is somewhat comparable to statistics (and often based on the latter), but takes it further in the sense that whereas statistics aims more at validating given hypotheses, in data mining often millions of potential patterns are generated and tested, in the hope of finding some that are potentially useful. It is a computationally much more intensive process. Examples of well-known data mining techniques are discovery of association rules (which properties of individuals are typically associated with each other?); building predictive models (decision trees, rules, neural nets, evolutionary algorithms) that can be used to predict unknown properties of individuals; building probabilistic models that summarize the statistical properties of a database, etc.
Natural Computing
prof.dr. Thomas Bäck (head)
Natural computing focuses on algorithms gleaned from natural models, such as evolutionary computation, molecular computing, neural computing, cellular automata, and swarm intelligence to mention the most popular ones. The focus is on both foundations of those algorithms and their applications on challenging real-world tasks. This research is bundled in the Leiden Center for Natural Computing.
Natural Computing Group
Leiden Center for Natural Computing
Theoretical Computer Science
prof.dr. Grzegorz Rozenberg (head)
The Theoretical Computer Science group is part of the Algorithms and of the Foundations of Software Technology clusters.