We do research on robot manipulation driven by state-of-the-art machine learning methods. Over the last decade the research on robot learning and human-robot skill transfer has progressed significantly. Our research is focused on novel machine learning approaches that combine learning by imitation with reinforcement learning to achieve higher levels of dexterity in manipulating various objects, including rigid and soft objects, single- and dual-arm manipulation, whole-body manipulation, visuospatial skill learning, etc.