Ad hoc ITEE PhD courses
Some ITEE courses are organized in conjunction with other PhD programs hosted by Departments of the Polytechnic and Fundamental Sciences School of the Federico II University
Academic year 2022-23
| Course title | Period | Lecturer | Course Description / Syllabus | Venue / Organizer(s) | CREDITS |
|---|---|---|---|---|---|
|
Artificial Intelligence and Natural Language Processing |
25-27-29/09 - 02-04/10/2023 | Prof. Francesco Cutugno, dr. Dr. Maria Di Maro, prof. Antonio Orilia, prof. Vincenzo Norman Vitale |
The course introduces the new vision of Natural Language Processing (NLP) considering the recent revolutions in the field. The advent of Large Language Models like ChatGPT has brought huge changes in the way we all see AI but it has also increased expectations and “noise” in people’s minds. At the same time, we observed different reactions from experts in the field, who were forced to specify the pros and cons of this revolution, and from non-experts who suddenly became proficient in their own view. In this perspective, we decided to offer to the doctoral school, and anyone else interested, a series of lectures on the foundations of modern NLP and aspects related to AI. There will be a final assessment. |
prof. Francesco Cutugno - DIETI - Unina |
3 |
|
Percorso per il rafforzamento delle competenze sulla progettazione europea |
14-28/09 12-26/10 09-23/11/2023 |
Dr. Tommaso FOGLIA, Dr. Federico PORCEDDA. Dr. Veronica ROCCO |
L'Ateneo Federico II ha aderito all'attività di formazione per il rafforzamento delle competenze del proprio personale docente e ricercatore e per i partecipanti ai corsi di dottorato di ricerca sulla progettazione europea, offerto dal Ministero dell'Università e della Ricerca, nell'ambito del PON Ricerca e Innovazione 2014/2020 (REACT-EU) |
Ministero dell'Università e della Ricerca, Ateneo Federico II
|
0,4 CFU per ciascun modulo da 2 h 0,6 CFU per ciascun modulo da 3 h |
|
Big Data Architecture and Analytics |
26-29/06 06-07-10-12-14-19-20/07/2023 | Dr. Giancarlo Sperlì, DIETI |
The aim of the course is to investigate Big Data methodologies and architectures for supporting analytics in different application domain from different point of views. In particular, the course provides an analysis about Big Data Management and Data Analytics Lifecycle, with reference to the design of large and complex data systems. Furthermore, the course focuses on the processes of ingestion, modelling, analysis and visualization about Big Data. Possible applications of these methodologies and architectures for different case studies (i.e., health, industry 4.0, social media and 5G networks) will be discussed at the end of this course. There will be a final assessment. |
DIETI ITEE - ICTH - CQB PhD programs |
5 |
|
Scienza moderna e disciplina giuridica dell'Intelligenza Artificiale |
07-09-14-16-21-23-28-30/06 – 06-07-10/07/2023 | prof. Lucio Franzese - DIETI - Unina |
The course investigates the structure of scientific knowledge, the way in which science proceeds, starting from the intuition of Galileo Galilei according to whom "the book of nature is written in mathematical language, and the characters are triangles, circles and other geometric figures”, which gave rise to the development of modern science. Referring to contemporary scientists and epistemologists, the hypothetical-deductive character and the operational function of scientific reflection will be highlighted, the aporias of which can be identified and overcome through philosophy, which etymologically expresses the love of knowledge. In particular, the claim of science to grasp the truth while it masters the phenomena it deals with will be refuted: scientia propter potentiam. The legal system represents the field in which the distinction between science and philosophy will be used. Modern legal science identifies law with the law, understood as auctoritas non veritas facit legem. In this way, however, the complexity of contemporary law expressed by economic and technical globalization escapes. Reducing the right to the law would not understand, on the one hand, the new lex mercatoria and, on the other, the regulation of the digital world. There will be a final assessment |
prof. Lucio Franzese - DIETI, Unina | 6 |
|
Academic Entreprenuership |
29-31/05 - 05-15-20-22/06/2023 | prof. Pierluigi Rippa, Silvia Cosimato, Nadia Di Paola - DIE Unina | prof. Pierluigi Rippa - DII, Unina | 4 | |
|
The Linear Parameter Varying approach: theory and application |
25-29-30/05 - 01/06/2023 |
prof. Olivier Sename Grenoble Institute of Technology
|
This course is concerned with Linear Parameter Varying (LPV) systems. In the first part we will provide definitions of such systems, as well as some modelling methods to get LPV systems state space representations from physical systems or from non linear models. Then properties such as controllability, observability and stability will be defined and some characterizations will be presented and discussed. The second part deals with control design methods for LPV systems. We will mainly put the focus on the referred to as polytopic and grid-based approaches, for which state feedback and dynamical output feedback control design methods will be given. The synthesis of state observers will also be considered. The third part is dedicated to the application of LPV methods to automotive systems. Two main cases will be presented: the modelling and control of semi-active suspension systems, and the multivariable control of Vehicle Dynamics. The objective will be to see different ways to use the potential of LPV approaches in realistic cases. The last part will be dedicated to the training phase in Matlab/Simulink in order to be able to model, analyze, control and simulate LPV systems for some simple examples.
There will be a final assessment |
prof. Luigi Glielmo - DIETI, Unina | 4 |
|
I pilastri della trasformazione digitale |
17-18/4 – 5-8-10/5/2023 |
dr. Francesco Tortorelli |
La progettazione di sistemi informativi complessi sotto la responsabilità di più organizzazioni, in settori quali sanità, trasporti e agricoltura, richiede un approccio metodologico e una sensibilità agli aspetti regolatori. Il corso illustra il contesto metodologico, funzionale e regolatorio per iniziative di trasformazione digitale, obbligatorio quando almeno uno degli attori è una pubblica amministrazione, e in molti casi anche tra privati. Il corso tratta i principi e l’applicazione dell’interoperabilità, il quadro regolatorio europeo e nazionale del settore, con particolare riguardo ai servizi che garantiscono, con valore legale e probatorio, le transazioni digitali (identificazione di soggetti e organizzazioni, trasmissione di documenti, sottoscrizione di documenti e conservazione di documenti). Il corso prevede una prova di valutazione finale.
|
prof. Nicola Mazzocca - DIETI, Unina | 3 |
|
Design of Extended Reality Software Systems |
Spring/Summer 2023 |
Dr. Domenico Amalfitano, prof. Anna Rita Fasolino |
The course introduces Extended Reality (XR) Software Systems to the researchers working in ICT and health domains, and presents software engineering solutions for specifying the requirements, designing, implementing, and evaluating the quality of such software systems. At the same time, the module will show the new research trends in the field of Extended Reality Software Systems and its novel applications in industry.
|
DIETI ITEE - ICTH PhD programs |
4 |
| How to boost your PhD | 11-18-25/01 - 1-8-15-22/02 - 1/03/2023 | Prof. Antigone Marino |
Technical skills are the first ingredient for a successful career, but often the competition with others is played on other skills.
This course covers training on soft skills, aiming to widen the PhD student spectrum.
|
DIETI ITEE - ICTH - CQB PhD programs |
4 |
|
Electronic Scan Antennas for Radar Signal Processing Applications |
27-28/02/2023 03/03/2023 |
Dr. Enzo Carpentieri |
This course will discuss the applications of Electronic Scanning Antennas in the Radar field and will provide the students with a brief introduction and a review of the main techniques/algorithms that can be applied for target filtering, beamforming, and detection. After a theoretical part, the attention will be shifted to some specific examples with emphasis on solutions proposed in practice. At the end of each lecture, students are encouraged to start a discussion on possible alternative techniques or solutions. |
Prof. A. De Maio, Dr. V. Carotenuto - DIETI, Unina | 2 |
|
Using Deep Learning properly |
10-12-17-19-24/01/2023 | Dr. Andrea Apicella, DIETI |
Designing and implementing a Deep Learning system is not an easy task. |
DIETI ITEE PhD |
4 |
|
IoT Data Analysis |
09-13-16-20-23-27/01/2023 | Dr. Raffaele Della Corte, DIETI |
This course will present advances on Data Analysis with emphasis on its adoption in the Internet of Things environments, where vast amounts of data are generated from multiple and heterogeneous data sources. The course will provide the students with the concepts and advanced techniques for analyzing field data (such as computer logs, event trace, system level metrics, IoT data) to understand the behavior of an IoT system from a dependability point of view. The course puts the basis for the development of analysis frameworks the students can leverage in their own research field. The final assessment will require students to prepare a good quality presentation about the potential application of the provided Data Analysis concepts and techniques to their research activities. Student’s presentations will take place in the last lesson. Details about the presentation format and schedule will be given during the course. |
DIETI ITEE PhD |
4 |
|
On the challenges and impact of Artificial Intelligence in the Insurance domain |
21-24-28-30/11/2022 |
Dr. Lorenzo Ricciardi Celsi, PhD, MBA |
The course introduces how Artificial Intelligence (AI) is reshaping insurance, ranging from multimedia forensics to car crash detection based on telematics data. In addition to a general introduction to the field of AI applications in insurance, we discuss a few topics that are widely considered very effective and promising. We will also discuss the results obtained with respect to some relevant use cases. In particular, (i) the role of deep learning in multimedia forensics, and (ii) the concept and benefits of explainable AI will be discussed. There will be a final assessment |
DIETI ITEE PhD |
3 |
|
Virtualization technologies and their applications |
30/01 03-06-10-13-20-24-27/02 03/03/2023 |
Dr. Luigi De Simone, DIETI |
The course presents advanced virtualization technologies used today for both research and industrial applications, including embedded systems, networking, and telecom equipments. The course will provide the students with the basis for developing experimental testbeds and novel systems with high-performance and reliability properties in their own research field. Every lesson consists of a first part on the overview of the specific virtualization technology, and a second part on a hands-on session to show how to use that technology in practice. At the end of the lesson, students are encouraged to start a discussion on why and how to adopt that virtualization approach in their research activities. The course foresees ten two-hours lectures split in four to five weeks, two to three days per week. Course syllabus |
DIETI ITEE PhD |
5 |
|
Statistical data analysis for science and engineering research |
06-08-10-13-15-16/02/2023 |
Prof. Roberto Pietrantuono, DIETI |
The course provides an overview of the experimental design and data analysis and is intended to teach PhD the use of statistical methods and data analysis as part of their research. More specifically, the course introduces the main elements required to plan robust experiments according to the Design of Experiment (DoE) methodology and the basic statistics required to properly analyse the resulting data depending on the experimental settings. The course will also treat data analysis under unplanned experiments with observational data. Common errors in experimental planning and misuse of statistics will be highlighted throughout the course. The course will show the application of what explained on exemplifying science and engineering research problems. The course foresees six two-hours lectures split in three weeks, two days per week. An additional seventh lecture will be devoted to the final assessment. |
DIETI ITEE PhD |
4 |
|
Matrix Analysis for Signal Processing with MATLAB Examples |
Spring 2023 |
Proff. Antonio De Maio, Augusto Aubry, Dr. Vincenzo Carotenuto, DIETI |
The course provides an overview on some topics in matrix theory together with their intrinsic interaction with and application to signa processing. The most important and "useful" tools, methods, and matrix structures are emphasized and complemented with MATLAB examples. The lectures cover basic matrix structures and operations, the concept of matrix norm, orthonormal matrices, singular value decomposition, positive (negative) semidefinite matrices and their eigenvalue characterization, Schur complement, matrix gradient, least square problems, Kronecker product. The course foresees four two-hours lectures split in two weeks, two days per week. An additional fifth lecture will be devoted to the final assessment. |
DIETI ITEE PhD |
3 |
|
Cooperative and Non Cooperative Localization Systems |
Spring 2023 |
Proff. Antonio De Maio, Augusto Aubry, Dr. Vincenzo Carotenuto, DIETI |
The course provides an overview about radiofrequency cooperative and non- cooperative localization systems. The first part introduces basic concepts on radar systems and a variety of applications leveraging radar technology. The second part provides the working principles of diverse radiolocatization techniques and presents fundamental issues on the satellite navigation systems. The third and last part is focused on two important practical systems: the Secondary Surveillance Radar (SSR) for air traffic control and the Automatic Identification Systems (AIS) for maritime localization. There will be a final assessment. |
DIETI ITEE PhD |
3 |
|
Strategic Orientation for STEM Research & Writing |
Summer 2023 |
Dr Chie Shin Fraser |
In a professional environment where the effective public communication and dissemination of research findings are deemed at least as important as the research itself, researchers, academics, and experts especially in the STEM domains are increasingly expected to perform to and live by the oft-repeated motto “publish or perish”. This course instills participants with a strategic perspective as a prerequisite for sharpening research focus and developing the core competency of effective expert/professional writing and communication, particularly with a view to getting published. There will be a final assessment. |
DIETI ITEE PhD |
3.6 |
|
Operations Research: Mathematical Modelling, Optimization Methods and Software Tools |
Autumn 2023 | Dr Adriano Masone, DIETI |
The course teaches how to build mathematical models of optimization problems, to be able to classify models and to know the mathematical foundations of algorithmic techniques that allow them to be solved. Furthermore, the course includes a laboratory part with emphasis on modelling and the use of commercial optimization software. Finally, optimization problems arising from real case studies in different application fields, and the related solution approaches, will be discussed at the end of this course. There will be a final assessment. |
DIETI ITEE PhD |
4 |
|
Scientific writing |
Summer 2023 | Prof. Stefano Russo, DIETI |
The course covers the process of peer- reviewing and the tasks involved in reading, reviewing and writing scientific articles and their parts: abstract, introduction, original contributions, research method, experimentation, discussion of results, threats to validity, conclusions. There will be a final assessment. |
DIETI ITEE PhD |
3 |
|
Machine Learning for Science and Engineering Research |
Summer 2024 |
Proff. A. Corazza, F. Isgrò, R. Prevete, C. Sansone, G. Pezzulo |
The course introduces the main topics in machine learning for both supervised and unsupervised approaches. In addition to a general introduction to the field, we discuss a few topics that are widely considered very effective and promising. In particular, the concept of explainable AI will be discussed, with special attention to the case of neural networks. There will be a final assessment. |
DIETI ITEE PhD |
5 |
|
Data Science for Patient Records Analysis |
Spring - Summer 2023 |
Prof. Marcello Cinque, Prof. Carmela Bravaccio, UNINA |
The course provides an overview of data science methods and tools, from data preparation to data modeling and validation, and it is intended for PhD students in science and engineering disciplines who need to use machine learning and data analysis as part of their research. The course focuses on the application of the analyzed methods for the analysis of patient records, in the context of a real case study. There will be a final assessment. |
DIETI ICTH - ITEE PhD Programs |
2,5 |
|
From observability to privacy and security in discrete event systems |
Winter 2023 (38th cycle, second year) |
Prof. G. De Tommasi, DIETI - Prof. F. Basile, Univ. of Salerno - Prof. C. Sterle, DIETI |
The course tackles several topics related to the state estimation of Discrete Event Systems (DES) in presence of events whose occurrence cannot be detected, although their effect on the system is assumed to be known, and hence modeled. Starting from the state estimation problem for non- deterministic (uncertain) DES, the notion of diagnosability for unobservable fault will be introduced. Both graph-based and optimization- based techniques to assess diagnosability and to perform fault detection will be presented. If the unobservable events are used to model secret behaviors, the techniques adopted for state estimation and fault diagnosis can be further extended to deal with security issues such as non- interference and opacity. All the aspects will be framed both in the context of finite state automata (i.e., when dealing with regular languages), and for Petri nets, being these modeling tools the most used ones in the context of control engineering and industrial automation. At the end of the course there will be a final assessment. |
DIETI ITEE PhD |
5 |
|
Advanced Modelling and Control of Energy Storage Systems, Power Converters and Electrical Drives |
Spring 2024 (38th cycle, second year) |
Prof. Ciro Attaianese, Prof. Diego Iannuzzi, DIETI |
The course provides an advanced modelling and control of electrical energy storage systems and drives using methods and analysis as part of their research. More specifically, the course introduces the main elements required to model, design, and control the storage devices, power converters and motors considering the whole electrical system as smart actuator. The course will show the application of what explained on exemplifying science and engineering research problems. The course will be split into two modules where the first one is focused on Energy Storage Systems and integration with power converters, the second one is focused on smart electrical drives. There will be a final assessment. The course foresees twelve two-hours lectures split in six weeks, two days per week. |
DIETI ITEE PhD |
6 |
|
Imprenditorialità Accademica |
Spring 2023 | Prof. P. Rippa, DII |
Il corso di "IMPRENDITORIALITA' ACCADEMICA", della durata di 10 h e seguito da un laboratorio di Business Plan (vedere sez.: Altre attività didattiche), è impartito da docenti di Ingegneria Gestionale della Scuola Politecnica e delle Scienze di Base, ed è finalizzato alla valorizzazione dei risultati della ricerca. Il corso fornisce una panoramica sui modelli di valorizzazione economica dei risultati della ricerca scientifica, nonché sugli strumenti di tutela della proprietà intellettuale di matrice accademica. E' prevista una prova finale. The course is in Italian language. |
Scuola Politecnica e delle Scienze di Base |
4 |
PhD Courses shared with MSc curricula or with other PhD programs
List of courses offered to ITEE PhD students, provided they have not attended them in their past career. The list includes advanced courses shared with the 7 master degrees offered by the DIETI department (courses of student's own choice, typically in the last year of MSc curricula).
ITEE PhD students may attend courses from the non-exhaustive list below and claim the corresponding credits, typically in the first or second year of their PhD program.
Students interested in attending other courses offered in MSc programs of the Federico II University of Napoli (including in master degrees of UniNA departments different form DIETI), or in other Universities, need to inform the ITEE Coordinator before attending them and claiming corresponding credits.
IMPORTANT:
ITEE students attending courses shared with master degrees of the Federico II University, HAVE TO ENROLL into the course contacting the lecturer and informing the ITEE Secretariat.
| Code | Course title | Credits | Lecturer | SSD | Semester |
|---|---|---|---|---|---|
| U3514 | Machine Learning - Statistical learning | 6 | A. Corazza | INF/01 | I |
| 15809 | Social, ethical, and psychological issues in artificial intelligence | 6 | G. Tamburrini | INF/01 | I |
| U3525 | Biometric systems | 6 | Daniel Riccio | INF/01 | II |
| U3536 | Human Robot Interaction | 6 | S. Rossi | INF/01 | I |
| U3515 | Neural networks and deep learning | 6 | R. Prevete | INF/01 | II |
| 30220 | Dispositivi e sistemi fotovoltaici | 9 | S. Daliento | ING-INF/01 | I |
| 30028 | Misure a Microonde ed Onde Millimetriche | 9 | C. Curcio | ING-INF/02 | II |
| U2253 | Progettazione in sicurezza elettromagnetica dell'ambiente ospedaliero | 9 | G. Ruello | ING-INF/02 | II |
| U1777 | Tomografia | 9 | A. Liseno | ING-INF/02 | I |
| U3578 | Ottica e Iperfrequenze | 9 | A. Capozzoli | ING-INF/02 | II |
| 16250 | Componenti e Circuiti Ottici | 9 | A. Capozzoli | ING-INF/02 | II |
| U2758 | Nanotechnologies for Electrical Engineering | 6 | C. Forestiere | ING-IND/31 | I |
| U2480 | Electrodynamics of Continuous Media | 9 | C. Serpico | ING-IND/31 | II |
| U0991 | Introduzione al Ferromagnetismo | 3 | C. Serpico | ING-IND/31 | II |
| U3483 | Introduction to Quantum Circuits | 9 | G. Miano | ING-IND/31 | I |
| 15259 | Modelli numerici per i campi | 9 | G. Rubinacci | ING-IND/31 | I |
| U2738 | Generatori, convertitori e dispositivi di accumulo | 6 | D. Iannuzzi | ING-IND/32 | I |
| 04247 | Elaborazione Numerica dei Segnali | 6 | G. Scarpa | ING-INF/03 | II |
| U2265 | Tecniche di elaborazione dei segnali per la bioingegneria | 9 | A. De Maio | ING-INF/03 | II |
| 11497 | Teoria dell’Informazione | 6 | M. Lops | ING-INF/03 | I |
| U1564 | Radiolocalizzazione e Navigazione Satellitare | 6 | A. Aubry | ING-INF/03 | I |
| 31687 | Sistemi radar | 9 | A. De Maio | ING-INF/03 | I |
| U3532 | Data Analytics | 6 | A. Tulino | ING-INF/03 | I |
| U2246 | Visione per Sistemi Robotici | 9 | A. Verdoliva | ING-INF/03 | II |
| U3584 | Quantum Information | 6 | A.S. Cacciapuoti | ING-INF/03 | I |
| U2325 | Robotics Lab | 6 | V. Lippiello | ING-INF/04 | II |
| U1954 | Identificazione e Controllo Ottimo | 6 | F. Garofalo | ING-INF/04 | II |
| U2331 | Field and service robotics | 6 | F. Ruggiero | ING-INF/04 | II |
| U0907 | Analisi e Prestazioni di Internet | 6 | A. Pescapè | ING-INF/05 | II |
| U0603 | Big Data Analytics and Business Intelligence | 6 | V. Moscato | ING-INF/05 | II |
| U2343 | Cloud and datacenter networking | 3 | R. Canonico | ING-INF/05 | II |
| 06649 | Intelligenza artificiale | 6 | Flora Amato | ING-INF/05 | II |
| U2256 | Machine Learning e Big Data per la Salute | 9 | V. Moscato | ING-INF/05 | I-II |
| 33774 | Metodi formali | 3 | V. Vittorini | ING-INF/05 | II |
| 28552 | Protocolli per Reti Mobili | 6 | S. Avallone | ING-INF/05 | II |
| U0604 | Secure Systems Design | 6 | V. Casola | ING-INF/05 | I |
| U3548 | Distributed Systems | 6 | S. Russo | ING-INF/05 | I |
| U2506 | Software security per sistemi industriali | 3 | D. Cotroneo | ING-INF/05 | I |
| U3554 | Software security | 6 | R. Natella | ING-INF/05 | II |
| U3573 | Data Management | 6 | Carlo Sansone | ING-INF/05 | I |
| U2643 | Hardware and Software Architectures for Big Data – Mod. A | 6 | E. Masciari | ING-INF/05 | I |
| U2644 | Hardware and Software Architectures for Big Data – Mod. B | 6 | V. Moscato | ING-INF/05 | II |
| U1592 - U1593 | Biomedical Imaging and Computer Interface for Biological Systems | 12 |
M. Cesarelli, P. Bifulco |
ING-INF/06 | II |
| U2248 | Strumentazione e Ingegneria Clinica | 9 | P. Bifulco | ING-INF/06 | II |
| U2653 | Incertezza dei dati | 6 | L. Angrisani | ING-INF/07 | II |
| U1881 | Instrumentation and Measurements for Smart Industry | 6 | P. Arpaia | ING-INF/07 | II |
| 30040 | Misure su sistemi wireless | 9 | L. Angrisani | ING-INF/07 | II |
| 16227 | Ottimizzazione Combinatoria | 6 | P. Festa | MAT/09 | II |
| U2338 | Statistical Learning and Data Mining | 6 | R. Siciliano | SECS-S/01 | I |