Algorithms are one of the foundations of computer science. Every computational task a computer performs is based on some algorithm, be it for data processing and retrieval, for artificial intelligence, for computer simulations, and much more. Good algorithms are efficient and effective: they should do what the user wants, and do it fast. In the Algorithms division, we explore a wide range of topics, ranging from data collection, storage and preparation, to unsupervised learning to extract patterns from data, and from the fundamental complexity of graph problems, to efficient computations for real life applications. Our research is based on developing new techniques and proving their properties using mathematical methods and through experiments with data.
The division is active in the international research community but has multiple collaborations with companies as well. Some examples are the Dutch Railways, QBuzz, and HERE Technologies.
- Fitting search methods and data mining and knowledge discovery
- Graph algorithms, fixed parameter tractability, and network science
- Optimization, logistics, and scheduling
- Data Intensive Systems, data preparation and curation
- Probabilistic reasoning and networks
- Computation for graphics, GIS, motion planning, and crowd simulation
- Emergent behaviour, transition and robustness properties of complex systems
- Algorithmic Data Analysis (Arno Siebes)
- Algorithms and Complexity (Hans Bodlaender)
- Data Intensive Systems (Yannis Velegrakis)
- Geometric Computing (Marc van Kreveld)
- Simulation of Complex Systems (Gerard Barkema)