During her PhD, Katrine Scheel Killmann researched how to efficiently find patterns in large and complex datasets. Many modern applications rely on clustering, a data mining technique that groups similar data points, but traditional methods are too slow for large datasets.

Katrine Scheel Killmann developed GPU-accelerated clustering algorithms that make these analyses significantly faster while ensuring correct reliable results. Her research focused on complex data types, such as movement data and high-dimensional data, and explored how consumer-grade graphics cards can be used for large-scale data analysis.

The new findings make it easier to analyse vast amounts of data quickly without access to expensive data centres, improving applications in fields such as transportation, biology, and social sciences.

The PhD study was completed at Department of Computer Science, Faculty of Natural Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Wednesday, 30 April 2025 at 13:00
Place: Building 5335, room 395, Department of Computer Science, Aarhus University, Åbogade 34, 8200 Aarhus N
Title of PhD thesis: Fast (Correct) Clustering in Time and Space using the GPU.
Contact information: Katrine Scheel Killmann, e-mail: katrine@scheel-nellemann.dk, tel.: +45 23934700
Members of the assessment committee:
Professor Peer Kröger, Institute of Informatics, Kiel University, Germany
Professor Yongluan Zhuo, Department of Computer Science, University of Copenhagen, Denmark
Professor Claudio Orlandi (chair), Department of Computer Science, Aarhus University, Denmark
Main supervisor: Professor Ira Assent, Department of Computer Science Aarhus University, Denmark
Language: The PhD dissertation will be defended in English

The defence is public.
The PhD thesis is available for reading at the Graduate School of Natural Sciences/GSNS, Ny Munkegade 120, building 1521, 8000 Aarhus C