My research interests are in optimization, data mining and decision making. In particular, my current work focuses on designing and developing techniques for:
data-driven decision making, characterized by ill-posed problems, noisy and incomplete data, uncertain and inconsistent information, concept drift, etc.;
optimization under uncertainty, where the problem to be optimized cannot be completely defined before the solution process.
Concrete applications of data-driven decision making and optimization under uncertainty are, e.g., the design of recommendation systems, that suggest content to the user based on partial and uncertain knowledge of her preferences, and the design of decision-making systems for the simultaneous optimization of conflicting objectives (multi-objective optimization).