The PhD program is structured into two curricula.

Curriculum in Electronics and Telecommunications

The research topics span the following disciplines.

Bioengineering (ING-INF/06).
Sensing and biosensing based on innovative materials. Wearable systems for biomonitoring. Analysis of biomedical signals and biomedical instrumentation.

Communications (ING-INF/03).
Signal processing and transmission. Systems for multimedia data processing and transmission and telecommunication networks.

Electrical and Electronic Measurements (ING-INF/07).
Study, implementation and metrological characterization of advanced measurement instrumentation based on digital signal processing. Hardware: architectures of large scale distributed measurement systems, along with the necessary synchronization techniques. Software: virtual instrumentation. Metrological characterization: Monte Carlo numerical procedures.

Electrical Engineering (ING-IND/31).
Methods for signal processing, aimed at studying complex, nonlinear, and chaotic systems. Participation in research programs focused on predicting events, analysis and synthesis of systems, identification, and optimization. Soft computing techniques such as artificial neural networks, fuzzy logic, and probabilistic computation.

Electromagnetic Engineering (ING-INF/02).
The research interest of the Applied Electromagnetics group (EMA) are the modeling, numerical full-wave simulations for the design and diagnostic of antennas; and for the design and analysis of Radiofrequency, Microwave and mm-Wave systems and circuits. The main field of applications are related to Telecommunications (e.g. 5G), Remote sensing and Radioastronomy. Furthermore, the group investigates the propagation of electromagnetic fields in urban environments and their interaction with biosystems. In particular, the analysis, modeling, design and development of systems for medical diagnostic applications, such as MRI, and therapeutic purposes, e.g. for hyperthermia in oncology, are activities carried out by the EMA group.

Electronics (ING-INF/01).
Diagnostic methods for failure analysis and reliability estimation in Microelectronics. Solid-state sensors and integrated circuits for signal processing and transduction. Organic Semiconductor Electronics; CMOS and organic based bioelectronic devices.

Power Electronics (ING-IND/32).
Energy Storage Systems. Research activity in this field focuses on the modeling and characterization of energy storage devices, new configurations of hybrid storage systems, and the development and implementation of management and control strategies and algorithms for stationary and vehicular applications (microgrids, electric propulsion systems).
E-mobility. Research in this area involves the development of strategies and algorithms for planning charging infrastructure for electric vehicles, management and control strategies for electric vehicle charging (grid-to-vehicle and vehicle-to-grid), sizing, management, and control of stationary energy storage systems for electric vehicle charging stations.

Curriculum in Computer and Systems Engineering

The research topics span the following disciplines.

Automatic Control (ING-INF/04).
Discrete event systems: supervisory control, Petri nets, fault diagnosis. Hybrid systems: analysis and optimal control. Control of mechanical systems. Automation and flexible manufacturing systems. Variable structure control. State estimation and control in uncertain systems. Simulation and control of constrained dynamical systems.

Computer Engineering (ING-INF/05).
Pattern recognition and computer vision: personal identity verification systems based on biometrics, advanced intrusion detection systems in computer networks, document categorization and spam filtering, content-based retrieval from image databases. Studies and applications of Extreme Programming and agile methodologies to software development. Models and simulation of financial markets and economics systems through heterogeneous agents. Applicative-cooperation architectures for e-government. Advanced methodologies for Blended Learning. Interactive digital television. Multiagent systems and hybrid genetic-neural architectures and systems with applications to bioinformatics, information retrieval, and text categorization.