| Course name | Course description | Teacher |
| Advanced electronic sensing devices | The course focuses on advanced sensors and transducers for electronic applications. The working principle of several different types of electronic sensors and their integration strategies with electronic systems will be discussed. At the end of the course, students will gain advanced knowledges about the working principles of several different classes of sensors with a strong focus on innovative devices and applications. | Link identifier #identifier__80535-1Lorenzo Colace |
| Quantum technology: toward quantum cryptography, teleportation, and quantum supremacy | The course provides a basic understanding of the principles of quantum technology and its main impact on high performance computation (qubits, superposition and quantum parallelism), on intrinsic security of communications (no cloning due to superposition collapse) and teleportation (entanglement effects). | Link identifier #identifier__128014-2Maria Cristina Rossi |
| Electromagnetic Methods for Periodic Structures | Full-wave numerical and semi-analytical methods for the solution of electromagnetic problems in periodic structures, such as artificial materials and periodic leaky-wave antennas, require the efficient and accurate computation of periodic Green’s functions (PGFs). The application of the Floquet-Bloch theorem reduces the computational domain of infinite periodic structures to a single unit cell, but leads to results that involve the numerical evaluation of very slowly or not converging series. Effective approaches for the numerical computation of the Green’s functions of periodic structures will be introduced. Electromagnetic Band-Gap (EBG) materials as periodic artificial materials will be introduced, and the methods of analysis: the plane-wave expansion method, and the description as reflection/transmission through a finite thickness unit cell. The two mechanisms for obtaining directive radiation from the coupling a source with an EBG will be deal with: the Embedded Source method and the Resonant Cavity Antennas. Finite periodic structures can be analyzed as a set of scatterers. In this sense a method that is quite powerful, accurate, and flexible for applications is the so- called Cylindrical-Wave approach. With this method the field scattered in a 2D geometry, that is of pratical use in several cases, can be analytically treated in terms of cylindrical waves. Use of plane wave expansions can allow the treatment of reflection and transmission properties also in presence of reflective plane interfaces. The method can be applied to georadar, through-wall radar, wireless power transfer for medical applications, and reflective intelligent surfaces for propagation channel analysis. | Link identifier #identifier__188545-3Giuseppe Schettini |
| Electromagnetic metamaterials and metasurfaces | The course is intended to provide students with advanced skills for the analysis and design of electromagnetic metamaterials and metasurfaces, with a specific focus on their use for the next-generation (beyond 5G) communication systems. A particular attention is devoted to the topic of reconfigurable and cognitive metasurfaces that are capable of sensing the electromagnetic conditions of the external environment and to adaptively adjust their behavior in real-time. | Link identifier #identifier__167542-4Alessio Monti
Link identifier #identifier__140701-5Filiberto Bilotti |
| New generation human-machine interfaces and their use in security and safety applications | The purpose of the course is to provide the student with an understanding of the issues involved in the design of a human-machine interface. The course includes an introduction of human-machine interaction systems, the analysis of usability aspects in safety and security application scenarios, the evaluation of the quality of experience, and design of a human-machine interface prototype. Immersive interaction systems based on multisensory 3D acquisition and rendering will be used in this course | Link identifier #identifier__162611-6Marco Carli |
| Information security | The objective of this PhD course is to present insights on aspects related to information security, considering processes and tools designed and deployed to protect sensitivedata by preventing or reducing the probability of unauthorized access, disclosure, modification, disruption, deletion, or corruption. The students will be presented with the fundamentals regarding the analysis, the design, and the implementation of biometric-based recognition systems, which exploit physical, behavioral, or cognitive human traits to differentiate among distinct subjects. Algorithms employed to process the considered characteristics will be outlined, focusing on specific machine learning and deep learning approaches. Cryptographic primitives able to secure sensitive data in distributed environments will be also discussed. |
Link identifier #identifier__155038-7Patrizio Campisi |
| Advanced Signal and Image Processing | The course aims to illustrate methods of signal and image digital processing for telecommunications and remote sensing purposes. Starting from a description of the major digital algorithms, applications to several fields of mobile and wireless telecommunications will be addressed, as well as the problems of detection and estimation of signals and images even under hidden information conditions. | Link identifier #identifier__179348-8Gaetano Giunta |
| Feature extraction and classification of biomedical data | Course objectives: The course aims at enabling the PhD candidate to develop in-depth expertise in the field of data mining, with specific reference to the techniques for feature extraction, classification and clustering, for applications in biomedical engineering. Program: Feature extraction problem: features in the time domain; features in the frequency domain; moments. Similarity and distance measures. Pre-processing: outliers detection and removal; dimensionality reduction (Factor Analysis, Principal Component Analysis, Independent Component Analysis). Supervised classification: Naive Bayes, Support Vector Machines, k-Nearest Neighbors, Decision Trees, Forests. Unsupervised classification (clustering): k-means, k-medoids and Partitioning Around Medoids. Applications to use cases with implementation in software environments (MATLAB, Python) |
Link identifier #identifier__23037-9Maurizio Schmid |
| Time-frequency, time-scale, wavelet methods | Aims To acquire knowledge on methods for the treatment of non-stationary signals, with particular reference to techniques for the extraction of information from two- dimensional time-frequency, time-scale spaces. Syllabus Fundamentals of spectral estimation Methods for parametric and non-parametric spectral estimation Wavelet transform and signal representation in the time-scale domain Time-varying autoregressive methods. |
Link identifier #identifier__192979-10Silvia Conforto |
| Quantum Phenomena and Quantum Systems | Superconductivity is a macroscopic quantum phenomenon with very different applications. The course aims at introducing the main roles of superconductivity in the fields of power applications, radiofrequency applications, metrology and quantum computing (from macroscopic to microscopic). The course presents first a short introduction to superconductivity and superconducting materials, and then a selection of the applications of superconductivity in the fields mentioned. | Link identifier #identifier__76960-11Enrico Silva |
| Surface investigation chemical techniques for biomaterials and biosensors | The course aims at illustrating the fundamental principles and applications of experimental techniques for surface characterization of materials of interest in the biomedical field, with particular attention to biosensors. Students will acquire skills that will allow them to identify the most appropriate experimental techniques to obtain chemico-physical information about complex materials. The writing of a report that develops and deepens some of the aspects covered in the course will constitute the evaluative moment of the course. | Link identifier #identifier__150340-12Giovanni Sotgiu |
| Machine learning and numerical techniques for inverse problems and design of electrical and electronic systems | The course provides the main numerical models for the design and simulation of electrical and electronic systems. The most important machine learning models and their use in the field of numerical modeling will be described. Furthermore, applications of finite element and finite difference calculus will be shown for the simulation of the main systems of electrical and electronic engineering. All the methods and techniques presented during the course will be applied and performed on the computer through different programming languages and software platforms. | Link identifier #identifier__78070-13Francesco Riganti Fulginei |
08 June 2023