Marco graduated in Mathematical Statistics and Data Management at the University of Genoa in 2016. During his Bachelor degree he completed a six months Erasmus period at the TU Dortmund, where he wrote his final thesis concerning the use of M-estimators for the detection of change points in time series models. In 2018 he obtained an MSc in Stochastics and Data Science at the University of Turin. His final thesis concerned the quickest detection of disorder times for the Ornstein-Uhlenbeck process. He is interested in stochastic analysis and especially in its applications. In his spare time he writes fantasy novels (in Italian).

Research project title:
Stochastic Optimal Control for problems arising in data science

Supervisor(s):
Alex Cox, Kari Heine

Project description:
Stochastic optimal control is a sub field of control theory that deals with the existence of uncertainty either in observations or in the noise that drives the system. Its aim is to design the path of the controlled variables that performs the desired task with minimum cost. Marco is studying problems where there is a data collection process, and a decision based on this information such as when to stop, or what information to collect. These problems are related to sequential detection problems and to uncertain stochastic control problems, where the law of the stochastic process driving the system is not known. Marco plans to investigate how these problems are related and to explore possible applications in data science, where it is fundamental to understand when, during a sampling procedure, enough samples have been collected to make a decision.