About

Lukas Miklautz is a PhD student (PraeDoc), at the Data Mining and Machine Learning research group at the Faculty of Computer Science University of Vienna, Austria. He focuses on new methods combining representation learning and clustering (Deep Clustering). Deep clustering methods combine unsupervised or self-supervised learning algorithms with clustering objectives to improve clustering performance. Deep clustering is applicable to many clustering paradigms like non-redundant clustering, ensemble clustering or subspace clustering. Lukas Miklautz contributed to several publications at top-level Data Mining and Artificial Intelligence conferences like ICDM or AAAI and is currently working on an application-oriented project in the digital humanities for clustering images of Early Medieval glass beads.