Claudio’s research examines the interplay between big data and mixed-integer (non linear) programming. This will lead to
1. the definition and solution of new optimization problems, arising from the inside gained in the data thanks to the application of machine learning principles, taking into account the end-user behaviour
2. new learning algorithms that can face more e-ciently the challenges linked to the large volume and variety of data collected through modern technologies
3. new heuristic algorithms to “intelligently” solve existing optimization problems.
Given its multidisciplinary nature, the fields involved in the research could be many, from new types of routing problems that will benefit from the knowledge gained from real-time data, to problems in the retail shopping context or medical healthcare just to cite a few.