I am a postdoctoral researcher in the Machine Learning Group of the Institute for Computing and Information Sciences at the Radboud University (The Netherlands), funded by the Radboud Excellence Initiative. I have received my Diploma degrees in Mathematics and Computer Science from the Westfälische Wilhelms-Universität Münster (Germany) and my PhD in Computer Science from the Carl von Ossietzky Universität Oldenburg (Germany).
My research interests include various topics in the field of data analysis (data mining, machine learning, algorithm engineering, ...) with applications for challenging large-scale scenarios in astronomy, text mining, energy systems, and others.
For an overview of past and current research projects, see here.
Fabian Gieseke, Justin Heinermann, Cosmin Oancea, and Christian Igel. Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. In Proceedings of the 31st International Conference on Machine Learning (ICML) 32(1). 2014, 172-180.
Fabian Gieseke, Tapio Pahikkala, and Christian Igel. Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. In Proceedings of the 5th Asian Conference on Machine Learning (ACML). 2013, 62-71.
Tapio Pahikkala, Antti Airola, Fabian Gieseke, and Oliver Kramer. Unsupervised Multi-Class Regularized Least-Squares Classification. In Proceedings of the 12th IEEE International Conference on Data Mining (ICDM). 2012, 585-594.
Fabian Gieseke, Joachim Gudmundsson, and Jan Vahrenhold. Pruning Spanners and Constructing Well-Separated Pair Decompositions in the Presence of Memory Hierarchies. Journal of Discrete Algorithms (JDA) 8(3):259-272, 2010.
A complete list of my publications can be found here.