Anne Driemel is an Assistant Professor in the Data Mining group at Eindhoven University of Technology (TU/e). Her work focuses on the computational geometry of curve similarity computation. She has a broad interest in high-dimensional algorithmic problems involving geometry, motivated by applications in geographic information science and data analysis. Anne’s primary goal is to design algorithms and data structures that are both practical and have provable performance. To this end, she combines classical worst-case analysis with approximation techniques and realistic input models. Her interests also include application of randomization techniques to obtain simple and effective solutions for computationally hard problems. She is especially interested in curve and graph similarity computations, ranging from mapping trajectories to road networks and clustering time series. Courses examine software, algorithms, control systems and theoretical computer science.
Anne Driemel received her PhD in Computing Science from Utrecht University in the Netherlands. She also holds a BSc and MSc in Computer Science from the Free University of Berlin, where she has also worked as a teaching assistant and scientific programmer. Anne has also worked as a Research Assistant at Dortmund University of Technology. In addition, she has been involved in projects at the University of Pennsylvania (GRASP Lab), Université Denis Diderot (Erasmus Program) and Rotary Youth Exchange Australia. Anne has been a visiting researcher at various Universities in the USA: Tulane University, New Orleans, University of Illinois at Urbana-Champaign (UIUC), Urbana and University of North Carolina at Chapel Hill. She has hosted workshops at a wide variety of locations, including Leibniz Center for Informatics, Wadern, Germany, Lorentz Center, Leiden, The Netherlands, Friedrich-Schiller Universität Jena, Germany and Princeton University, New Jersey, USA. Furthermore, she has acted as a referee at several international conferences including the International Workshop on Randomization and Computation and International Workshop on Graph-Theoretic Concepts in Computer Science.
Locality-sensitive hashing of curves33rd International Symposium on Computational Geometry (SoCG 2017) (2017)
Clustering time series under the Fréchet distance27th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2016) (2016)
On the expected complexity of Voronoi diagrams on terrainsACM Transactions on Algorithms (2016)
Jaywalking your dog : computing the Fréchet distance with shortcutsSIAM Journal on Computing (2013)
Approximating the Fréchet distance for realistic curves in near linear timeDiscrete and Computational Geometry (2012)
- Teachers Information Data Science
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