Current students

Traditional network optimization (NO) approaches fail to scale when dealing with large and complex instances. Novel methodologies integrating Machine Learning (ML) and NO promise to cope with otherwise untreatable problem instances thanks to their generalization and scaling capabilities. In this work, I will investigate new algorithms at the intersection of ML and NO to address complex resource allocation problems in the area of cross-layer optical networking and 5G network virtualization.