Xander Wilcke

Xander Wilcke is a Research Associate at the Faculty of Science, VU University, with affiliations to the Artificial Intelligence Research Associate group and the Network Institute. His work focuses on machine learning applied to knowledge graphs, data mining, and multimodal data analysis. He holds a PhD in Machine Learning for Heterogeneous Knowledge Graphs from VU University (2022).

Research Interests: Machine Learning on knowledge graphs, multimodal data integration, pattern discovery, and archaeological data analysis. His work emphasizes user-centric approaches and end-to-end learning frameworks for heterogeneous data. Recent projects include hypothesis creation support systems and timestamp vectorization techniques.

Awards:

• Best-Paper Award Nominee at KDIR 2020
• ICT.OPEN Best Poster Presentation Award (Runner-up, 2018)

Advising & Grants:

• Contributed to the development of the kgbench dataset collection
• Recipient of grants supporting knowledge engineering and data mining research

Active in academic collaborations, presenting at conferences like SEMANTICS 2024 and organizing workshops on social-historical knowledge graph analysis. Teaches courses on Knowledge Representation and Machine Learning for Graphs at VU University.