Main research interest
- algorithms for geographic data or other types of spatial data
- algorithmic questions arising in robotics and automation
- optimization problems related to networks
- I/O-efficient algorithms
- data structures for efficient retrieval of (in particular) spatial data
Our goal is to develop algorithms and data structures that have a firm theoretical basis, with guarantees on their efficiency and on the quality of the computed solutions, which are also effective in practice.
Kulicke & Soffa is a leading provider of semiconductor packaging and electronic assembly solutions. We have worked together with the optimizer team from their Eindhoven branch to further improve the efficiency of their pick-and-place machines.
An increasing amount of movement data are being collected in a wide range of applications. Focusing on applications in animal tracking we have worked together with ecologists to develop algorithms for trajectory analysis that help them understand animal behavior.
- Networks funded by Dutch Ministry of Education, Culture and Science
The goal of Networks is to address the pressing challenges posed by large-scale networks with the help of stochastics and algorithmics. The focus is on modeling, understanding, controlling and optimizing networks that are complex and highly volatile. Partners: TU/e, University of Amsterdam, University of Leiden, CWI.
- A framework for progressive, user-steered algorithms in visual analytics funded by NWO
The highly interactive visual analytics process bears unique challenges and requires a novel perspective on how to measure the performance of an algorithm. The aims of the project are to develop algorithms, which (i) give a fast response and then refine the solution progressively, (ii) provide the user with the means to steer the computation and are flexible enough to adapt to changing objectives, and (iii) provide a guarantee on the quality of their results.