Research topics

Kernel methods are a family of methods that have recently found a constantly increasing interest in the machine learning community. Commonly used methods, such as Gaussian process regression or Tikhonov regularization are in this category. These methods are used to estimate an unknown function from a dataset, and have found diffusion especially in the machine learning community...

Fault diagnosis is an established field of control systems. However, due to the intrinsic characteristics of the processes being monitored, fault detection and health monitoring methodologies need to be adapted for the particular problem at hand. The aim of this research area is to develop fault detection and condition assessment algorithms for industrial applications, drawing ...

This research area considers methodological developments of Model Predictive Control (MPC) schemes, with application to artificial pancreas control.

This research area is mainly devoted to preference-based and global optimization schemes.

This research activity consists in the study of a new paradigm for automatic algorithmic trading started by Professor B. Ross Barmish that aims to treat stock trading from a control theory point of view. Within this approach robust performances are seeked against external disturbances and some levels of performances are guaranteed under certain assumptions. The main innovation ...