My research is focused on machine learning problems with geometric flavor. The symbiosis between data-driven and model-driven methods opens up new and exciting possibilities to overcome limitations in the new era of machine learning.  The data we consume have a unique structure which we can further exploit in learning paradigm used, for example, in computer vision, medical imaging and robotics.