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- faculteit der exacte wetenschappen ( business, web en media ), faculteit der economische wetenschappen en bedrijfskunde ( ruimtelijke economie )
- PhD Student
In 2013, Xander Wilcke graduated at the Vrije Universiteit Amsterdam.
During his study, he focussed on Artificial Intelligence with a specialization in Machine Learning, Data Mining, and Distributed Computing. For his master thesis, he joined the Smart Bandits project team at the Dutch National Aerospace Laboratory (NLR). There, he used his skills to help improve the behaviour of simulated agents for use in pilot training.
As of 2014, Xander holds the position of a PhD candidate at the Vrije Universiteit Amsterdam, more specifically within both the Department of Computer Science and the Spatial Information Laboratory (SPINlab). His research centers on the use of novel Machine Learning techniques for learning from graph-based knowledge systems build upon predicate logic. Specific emphasis is being placed on Neural Networks and Deep Learning, with data sets encompassing Linked Open Data and related Semantic Web resources.
- Machine Learning
- Deep Learning
- Neural Networks
- Evolutionary Computing
- Wilcke, W.X. (2015). Learning an Optimized Deep Neural Network for Link Prediction on Knowledge Graphs. In J Hollmén & P Papapetrou (Eds.), Proceedings of the ECMLPKDD 2015 Doctoral Consortium (pp. 226-235).
Helsinki: Aalto University.
- Wilcke, W.X., Hoogendoorn, M. & Roessingh, J.J.M. (2014).
Co-evolutionary Learning for Cognitive Computer Generated Entities. In M Ali, JS Pan, SM Chen & MF Horng (Eds.), Modern Advances in Applied Intelligence Vol. 8482. Lecture Notes in Computer Science (pp. 120-129).
Springer International Publishing.