Within machine learning and AI, we adapt existing and develop new machine learning algorithms to tackle open questions in the applications domains of itec. We mainly focus on non-standard supervised and semi-supervised learning tasks, such as multi-output prediction, time-to-event prediction and interaction prediction. We typically target three goals in our methods: predictive performance, efficiency and interpretability.