Arber Qoku is a doctoral candidate in bioinformatics. His research focus includes developing statistically sound and computationally efficient latent variable models for comprehensible and scalable integration of multi-omics data. During his studies of Data Science (M.Sc.) at LMU Munich, he joined the Machine Intelligence Research Group at Siemens AG where he was exposed to an array of data science projects in the domain of information retrieval. This collaboration was finalised with a master thesis in the topology optimisation of tensor-based decompositions, where he developed compression methods for significantly reducing the memory usage of deep neural networks while maintaining the expressive power of the model.