The focus of our research in the machine learning group at the IGL lies at the intersection of machine learning and neuroscience. Machine learning methods utilize brain-inspired architectures which involve deriving optimized computational models that learn information directly from data. These fast-growing methods have witnessed a tremendous amount of attention in diagnostic, prognostic and predictive analytics that aid in decision-making and neurosurgical planning. We aim at exploiting cutting edge deep learning methods for different studies like brain automated tumor segmentation and classification, preoperative mapping of eloquent brain function as well as prediction of postoperative result, using large population studies with multimodal imaging data integrating physiological data.