In our spatial world, much of the data we generate is geometric. It is a great challenge to develop algorithms for dealing with these data.
Kevin Buchin is an Associate Professor in the Algorithms group at Eindhoven University of Technology (TU/e). His work focuses on computational geometry. He has a broad interest in fundamental algorithmic problems as well as problems driven by applications such as geographic data analysis and robotics. Kevin’s primary goal is to develop algorithmic solutions that are both practical and provably efficient.
Kevin has made many contributions to the theory of geometric algorithms, including fast algorithms for the Delaunay triangulation in the transdichotomous model, for computing the similarity between curves, and for constructing geometric spanners. For all of these problems, he has also developed practically efficient algorithms. On the applications side, Kevin has contributed to spatial networks analysis, movement data analysis, and robot motion planning. He is in particular interested in geometric algorithms that integrate data uncertainty.
Kevin Buchin holds a PhD in Computer Science from the Free University of Berlin and an MSc in Mathematics from the University of Münster. He has also studied in Zurich, Prague, Leeds and Potsdam. He came to the Netherlands as a postdoctoral researcher at the University of Utrecht. Kevin has been working at the TU/e Department of Mathematics and Computer Science since 2009.
He is teaching at the TU/e and the Jheronimus Academy of Data Science in Den Bosch. For his teaching achievements, he has been awarded the education award of the study association of the department of Mathematics and Computer Science, and the TU/e-wide award for best Bachelor lecturer.
Locally correct Fréchet matchingsComputational Geometry: Theory and Applications (2019)
Computing the similarity between moving curvesComputational Geometry (2018)
Model-based segmentation and classification of trajectoriesAlgorithmica (2018)
Compact flow diagrams for state sequencesACM Journal of Experimental Algorithmics (2017)
Four Soviets walk the dog: improved bounds for computing the Fréchet distanceDiscrete and Computational Geometry (2017)
- Seminar algorithms
- Geometric algorithms
- Bachelor research project
- CS Research Honors project 2
- Kick-off meeting Data Science & Engineering
- CS Research Honors project 1
No ancillary activities