Algorithms and Software Technology (AST)
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The Algorithms and Software Technology program performs fundamental research in the following areas.
- Methods and techniques for algorithm design and analysis, with an emphasis on algorithms and architectures for large data volumes as well as on natural computing.
- Development of formalisms, methods, techniques and tools to design, analyze, and construct software systems and components.
We aim for application of our algorithms in medicine, bio- and chemoinformatics, engineering, and physics. The program has various groups:
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.
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.
Theoretical Computer Science
prof.dr. Grzegorz Rozenberg (head)
prof.dr. Farhad Arbab, prof.dr. Joost N. Kok (heads)
Software Technology focuses on the formal semantic foundations of software composition and coordination. Large software systems are difficult to construct and maintain due to their inherent complexity. Compositional techniques hold the key to breaking this complexity down to manageable levels. Composing systems out of independent components or services requires coordination of their interactions. Considerations for concurrency, distribution, mobility, and dynamic reconfiguration of systems, e.g., to upgrade or adapt to their changing environment, add to the complexity of a system and its interaction protocols. Coordination in Software Systems studies how complex systems can be constructed from independent components or services using a clear distinction between individual components or services, and the protocols for their coordinated interaction.
Section Software Engineering
dr. Michel R.V. Chaudron (head)
Technology & Innovation Management
The aim of the Technology and Innovation Management (TIM) group is to understand the co-evolution of technology and social structures. It researches phenomena, especially the innovation process and the emerging information society, at the intersection of science and information technology on the one side, and social and business science on the other side. Work is grouped into the centre ‘˜Virtual Organisation‘™ which focuses on networked organizational forms and their management. This includes the design of ‘œFuture Work Spaces‘ and how they make use of information technology for new forms of productive collaboration. The centre ‘˜Innovation Management‘™ focuses on understanding innovation networks (or clusters) and how they contribute to the growth of new technology-based new ventures. One type of innovation networks that we study are Living Labs, especially the Knowledge Worker Living Lab. The group cooperates with CeTIM and its program office for international research cooperation and entrepreneurship. Junior researchers join the doctoral school, NITIM, a European network of universities.