Hours:
20 hours (5 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

In the last decades, electromagnetic metamaterials and metasurfaces have raised a huge amount of interest both in academic and industrial environments. The possibility to achieve unnatural and exotic properties confers to these solutions an unprecedented capability to shape, control and exploit the electromagnetic radiation for advanced applications. In the last years, the use of electromagnetic metamaterials and metasurfaces have been diffused also in 4.0 industry, increasing the diffusion and the development of innovative devices, sensors and productive processes.
The first part of the course will be directed to present the general theoretical aspects and modelization of metamaterials and metasurfaces, with a particular emphasis on the transversality among the different sectors where they found application. In the second part, practical test-cases of metasurfaces in advanced scenarios will be reported and discussed, along with design guidelines and tips to correctly dimension these tools. In details, sensing and imaging applications, useful for industrial, telecommunications and biomedical applications, and some examples about electromagnetic field manipulation will be described, as for instance absorption for lowering external disturbances at RF and microwaves, novel sensors and antennas, field filtering capability.

Course Contents in brief:

1. Electromagnetic modelization of metamaterials and metasurfaces
2. Derivation of practical design guidelines for 4.0 industry applications
3. Practical test-case: sensing and imaging for industrial and biomedical applications;
4. Practical test-case: radiation absorption/reflection for RF and MW coupling reduction and electromagnetic waves manipulation for stealth applications and next generation networks.

Schedule:

1. 06/02/2023: 09:00-13:00,14:20-17:00
2. 08/02/2023: 09:00-13:00,14:20-17:00
3. 09/02/2023: 09:00-13:00,14:20-17:00

Hours:
16 hours (4 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

The combination of the Internet of Things and Artificial Intelligence has made it possible to introduce numerous automations in our daily environments. Many new interesting possibilities and opportunities have been enabled, but there are also risks and problems. Often these problems are originated from approaches that have not been able to consider the users’ viewpoint sufficiently. We need to empower people in order to actually understand the automations in their surroundings environments, modify them, and create new ones, even if they have no programming knowledge.
The course discusses these problems and some possible solutions to provide people with the possibility to control and create their daily automations. It aims to allow attendees to gain knowledge and skills in addressing problems and solutions enabling end-user understanding, creation, control, monitoring, and debugging automations that can be deployed in their daily environments (home, office, shops, industry, …). It will provide a discussion of the possible solutions in terms of concepts, techniques, and tools, with particular attention to those supporting the trigger-action paradigm.

Course Contents in brief:

1. Introduction Course
2. The technological trends (IoT + AI)
3. The dark side of intelligent automations
4. Design criteria for transparency of intelligent environments
5. Trigger-action programming
6. Environments for end user creation of automations (Wizards, Block-based, Conversational Agents)
7. Augmented reality-based support for automation control
8. Real world deployment, execution, monitoring
9. Intelligent automation recommendations
10. Explainable end-user automation debugging
11. Usability and Accessibility Evaluation (Guidelines, methods, and how to design a user test and analyse its data)
12. Final Discussion

Schedule:

1. Day1 – time 9.00 – 13.00
2. Day2 – time 9.00 – 13.00
3. Day3 – time 9.00 – 13.00
4. Day4 – time 9.00 – 13.00

Hours:
20 hours (5 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor
Aula Riunioni del Dipartimento di Ingegneria dell’Informazione piano 6, Largo Lucio Lazzarino 1, Pisa

To register to the course, click here

Short Abstract:

The course aims at providing an introduction to the structural finite element modeling as a tool aided to design and analyze industrial applications and device. The course will therefore provide applicative examples with an emphasis to biomedical field, integrating theoretical lessons with hands-on sessions to learn the set up of Computer Aided Engineering (CAE) analysis through its main steps (pre-processing, solving, and post-processing).

Course Contents in brief:

1. Introduction to Finite Element Modeling
2. Workflow of Finite Element Analysis
3. Elements
4. Geometries and Meshing. From CAD to FEM
5. Materials
6. Analysis procedures
7. Contacts

Schedule:

1. 22/02/2023: 14:00 - 18:00 – Aula Riunioni piano Terra via Caruso
2. 23/02/2023: 9:00 - 13:00 – Aula Riunioni piano 6 Largo Lucio Lazzarino
3. 24/02/2023: 9:00 - 13:00 – Aula Riunioni piano 6 Largo Lucio Lazzarino
4. 27/02/2023: 9:00 - 13:00 – Aula Riunioni piano Terra via Caruso
5. 28/02/2023: 9:00 - 13:00 – Aula Riunioni piano Terra via Caruso

Hours:
20 hours (5 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

Based on the increasing advances in the fabrication and monitoring approaches of biomedical devices, innovative materials are being synthesized and explored to adapt and interact effectively with the specific biological environment. In this scenario, smart materials sensitive towards various stimuli such as temperature, pH, light, magnetic and electric field, can provide versatile and dynamically tunable platforms for the investigation and manipulation of several biological activities with very low invasiveness [1, 2].
Moreover, the use of advanced structured and responsive materials in combination with additive manufacturing technologies give the opportunity to design multi-functional and high-performance products. This novel approach aims to move beyond traditional design and manufacturing process towards 4D printing and the creation of dynamic structures, such as shape memory materials, with integrated functionalities [3].
The course thus aims to provide knowledge on the smart materials suitable for the design of 3D scaffolds, drug delivery systems and sensors for biomedical applications, with a special focus on devices created by means of additive manufacturing technologies.

Course Contents in brief:

1. Introduction to the use of smart materials for biomedical applications
   Recent advances in the design of 3D scaffolds for tissue engineering, drug delivery platforms and sensors with particular focus on the use of smart and biomimetic materials combined to additive manufacturing technologies.
2. Smart materials and mechanisms of action
   Presentation of new smart multifunctional or biomimetic materials for biomedical applications. Description of the specific mechanisms of actions considering endogenous stimulators such as pH, reactive oxygen species, hypoxia and enzyme, or exogenous stimulators such as temperature, light, ultrasound, radiation, and magnetic field. Special attention will be dedicated to smart biomaterials suitable for the design of biomimetic constructs.
3. Characterization of materials and devices
   Main analysis methods used to explore the material properties before and after the manufacturing process: 1) rheological studies aimed at investigating the visco-elastic properties of materials and able to support the optimization of the manufacturing process; 2) nanoindentation technique to explore the mechanical features and stability of materials and devices; 3) micro-computed tomography to identify the structural and compositional properties of the final devices.
4. Examples of applications
   Current applications, limitations, and future perspective of smart materials for the design of scaffolds and sensors. Presentation of different case studies to understand approaches and methods required to design scaffolds and sensors: synthesis of materials, manufacturing process and final validation of devices.

Schedule:

1. Day1 – 14:00 – 18:00
2. Day2 – 14:00 – 18:00
3. Day3 – 14:00 – 18:00
4. Day4 – 14:00 – 18:00
5. Day5 – 9:00 – 13:00

Hours:
16 hours (4 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

After an introduction to the main concept about ethics, related to norms, both in deontological and in behavioural meaning. Then ethical questions are shown in using techniques, interacting with technologies and living in a technological environments.
Some particular aspects of applied ethics in the field of ICT are discussed, focusing on the most relevant topics and approaches in contemporary debate.

Course Contents in brief:

1. Hints on philosophical and anthropological references
2. Responsibility and technological determinism.
3. Digital divide, multiculturalism and contemporary ethical debates
4. Privacy, security and democracy.
5. EU Rules for a trustworthy A.I.

Schedule:

1. 30/01/2023: 9:00 - 13:00
2. 31/01/2023: 9:00 - 13:00
3. 01/02/2023: 9:00 - 13:00
4. 02/02/2023: 9:00 - 13:00

Hours:
20 hours (5 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Largo Lucio Lazzarino 1, 6th floor, Pisa

To register to the course, click here

Short Abstract:

The Industrial Internet of Things (IIoT) will leverage on heterogeneous wireless network technologies to integrate in a seamless manner Cyber-Physical Systems (CPS) into existing information systems. Among the different solutions to ensure reliable and timely communication, the 6TiSCH architecture defined by the IETF is gaining research interest. 6TiSCH relies on the IEEE TSCH MAC protocol and includes the IETF suite of protocols to provide IPv6 connectivity for constrained wireless devices to integrate them with existing information systems. In this course, we will first introduce the different communication technologies for the IIoT and then we will carry out a comprehensive analysis of the 6TiSCH architecture to assess its performance and highlight the open research issues. In the last part of this course, we will overview how IIoT networks can be integrated with cloud platforms, introducing also the paradigm of fog computing to show how it can support industrial applications by enabling the execution of applications in proximity of CPS.

Course Contents in brief:

1. Introduction to the Industrial IoT (IIoT)
2. Overview of communication technologies for IIoT (5G, WiFi, TSCH, ...)
3. IETF 6TiSCH Architecture
   1. Protocols
   2. Scheduling (Centralized, Distributed, Autonomous, Hybrid)
   3. Performance
   4. Security
4. Integration of IIoT devices into Cloud platforms
5. Edge/Fog Computing for IIoT applications
6. Some relevant use cases

Schedule:

1. Day1 – 8:30-12:30
2. Day2 – 8:30-12:30
3. Day3 – 8:30-12:30
4. Day4 – 8:30-12:30
5. Day5 – 8:30-12:30

Hours:
16 hours (4 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

In this course, practical methodologies for marine data analysis and modelling will be presented.
The course will cover specific classes of problems in marine science and their corresponding solutions, adopting state-of-the-art computer science technologies and methodologies. The explained techniques will include:

1. Unsupervised approaches to discover patterns of habitat change and predict fishing vessel activity patterns: Principal Component Analysis and Maximum Entropy for feature selection; KMeans, XMeans, DBScan, and Local Outlier Factor cluster analysis; Singular Spectrum Analysis for time series forecasting;
2. Supervised approaches for species distribution prediction and invasive species monitoring: Feed-Forward Artificial Neural Networks, Support Vector Machines, AquaMaps, Maximum Entropy;
3. Bayesian models to predict fish stock availability in specific fishing areas;

These methods will be applied to marine data such as vessel transmitted data, species observation records, and catch and vessel time series that fall into the Big Data category. These data are crucial to safeguard food availability and economic welfare, which are fundamental to human life. For example, predicting the impact of climate change on species habitat distribution contributes to avoiding economic and biodiversity collapse due to sudden ecosystem change. Likewise, monitoring the effect of overfishing on fish stocks and marine biodiversity prevents ecosystem and economic collapse.
The explained techniques will address real use cases of the United Nations (FAO, UNESCO, UNEP, and others) for marine food and ecosystem safety and illustrate the new lines of research in this context. They are also general enough to be applied to Big Data of other domains. The analysed data have indeed general characteristics of Big Data such as constantly incrementing volume, vast heterogeneity and complexity, and unreliable content. For this reason, the methodologies will be illustrated in the context of the Open Science paradigm, characterized by the repeatability, reproducibility, and cross-domain reuse of all experimental phases.
The course will be interactive and made up of practical exercises. Attendees will use online environments to parametrize the models, run the experiments, and potentially modify the models. Experiment completion will be valid as the exam.

Course Contents in brief:

1. Marine data
2. Species observation and environmental parameter selection techniques
3. Distance and density-based cluster analysis for habitat and vessel pattern recognition
4. Artificial Neural Networks for species distribution modelling
5. Bayesian state-space models for population dynamics
6. Open Science approaches

Schedule:

1. Day1 – Introduction to marine data and Open Science methodologies – 9.00 – 13.00
2. Day2 – Data selection techniques and pattern detection – 9.00 – 13.00
3. Day3 – Supervised modelling of species distributions and invasions – 9.00 – 13.00
4. Day4 – Bayesian state-space models for population dynamics – 9.00 – 13.00

Hours:
20 hours (5 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor
Aula Riunioni del Piano 6 del Dipartimento di Ingegneria dell’Informazione, Largo Lucio Lazzarino 1, Pisa
Aula Virtuale il 12/12/2022

To register to the course, click here

Short Abstract:

The course will cover the main aspects of Edge Computing, from a both system level and practical perspective and with the aim to provide useful tool for engineers, research scientists and application developers. An initial technology overview will provide the description of MEC and related standards and industry associations working in the field, together with various open-source frameworks available. A particular emphasis will be given to the ETSI MEC standard (Multi-access Edge Computing), by mentioning as well other SDOs and the relationship with 3GPP for the definition of 5G systems. In particular, this course will introduce also innovative concepts like MEC Federation, and heterogeneous environments in multi-MNO domains, that are critical in many vertical market domains. A special focus will be given to automotive segment, and related MEC relevance from 5GAA (5G Automotive Association). The federation requirements, defined by GSMA OPG, will be presented together with the latest findings from impacted SDOs (ETSI, 3GPP) and open-source projects (LF). Additionally, an introduction of 5G-Advanced and their impacts on future MEC systems will be provided. A classroom exercitation will complete the course, where students will be asked to build their own application example exploiting MEC and based on the open-source software introduced during the course.

Course Contents in brief:

1. Edge Computing, Fog computing, Cloud computing
2. ETSI MEC Framework and Reference Architecture
3. MEC in 4G, MEC in 5G, MEC in WiFi networks
4. GSMA OPG and OPAG; LF CNCF Camara
5. 5GAA MEC4AUTO and global MEC deployments
6. MEC Federation (aspects from ETSI, 3GPP, GSMA, LF)
7. MCE Phase 3 and 3GPP Release 18
8. MEC Services, MEC Management, MEC Mobility
9. MEC APIs (Radio Network Information API, Location API, BW API, …)
10. Open-Source frameworks: OpenNESS, OpenAPI MEC APIs representations, ETSI Forge, MEC Sandbox, tools and MEC Ecosystem
11. Classroom exercise

Schedule:

Day1

05/12/2022: 11.00-18.00, Aula Riunioni Piano Terra, via Caruso

Topics:

1. Edge Computing, Fog computing, Cloud computing
2. MEC Framework and Reference Architecture [MEC003]
3. General principles for Mobile Edge Service APIs [MEC 009]
4. MEC Platform Application Enablement [MEC011]
5. GSMA OPG and OPAG; LF CNCF Camara
6. Classroom exercise – part 1

Day2

06/12/2022: 9.00-17.00, Aula Riunioni Piano Terra, via Caruso

Topics:

1. MEC in 4G, MEC in 5G, MEC in WiFi networks
2. MEC in NFV environment (MEC-017)
3. MEC support for Network Slicing (MEC-024)
4. MEC Management [MEC010-1][MEC010-2]
5. MEC Application and E2E Mobility (MEC-018, MEC-021)
6. Inter-MEC systems and MEC-Cloud systems coordination (MEC-035)
7. 5GAA MEC4AUTO and global MEC deployments
8. Software Development for MEC
9. MEC-027 – MEC support for Containers
10. Open Network Edge Services Software (OpenNESS)
11. Classroom exercise – part 2

Day3

07/12/2022: 9.00-17.00, Aula Riunioni Piano 6, Largo Lucio Lazzarino

Topics:

1. OpenAPI MEC APIs representations, ETSI Forge
2. MEC Sandbox, tools and MEC Ecosystem
3. MEC-012 – RNI API, MEC-013 – Location API, MEC-028 – WLAN Information API
4. MEC-016 – UE Application Interface, MEC-014 – UE identity API
5. MEC architecture variant for MEC Federation, inter-MEC system communication
6. MEC Federation deployment options
7. MEC Phase 3 and 3GPP Release 18
8. MEC Testing Framework (MEC-025), MEC Conformance Test Suite
9. Performance Assessment, Metrics Best Practices and Guidelines (IEG006)
10. MEC-026 – MEC support for regulatory requirements
11. Application Deployment, Application Walkthrough
12. Classroom exercise – part 3

Day4

12/12/2022: 14:00-17:00, Lezione da remoto

Topics:

1. Vertical segments: focus on automotive (MEC-022 “MEC support for V2X use cases”, and MEC-030 “MEC V2X API”)
2. MEC-015 – Bandwidth management API
3. MEC Federation enablement APIs (MEC 040)
4. MEC toward 6G systems
5. MEC in action: examples and trials
6. OpenNESS and 5G: integration with SimuLTE/5G
7. Classroom exercise – presentation of results

Hours:
16 hours (4 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

Optimization is central to solving problems in many engineering disciplines. Specifically in information engineering, the areas of signal and image processing, communications and radar systems, networking, control and robotics, and power systems benefit immensely from optimization theory and algorithms. Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions (or, equivalently, maximizing concave functions) over convex sets. This course will introduce essential elements of theory of convex optimization. While some problems may be solved analytically, often the rich body of numerical algorithms is needed in most practical settings. A rigorous coverage will be provided in best-known foundational numerical techniques that can be leveraged by students to understand and engage with the ever evolving body of numerical methods in the literature. Finally, applications will be discussed in signal processing and machine learning as compelling real-world problems.

Course Contents in brief:

Day 1 ( 4 hours)

Part 0: Linear Algebra Review

Part I: Theory

1. Introduction to mathematical optimization, cost function development, identification of key issues in formulating and solving optimization problems

2. Convex Sets: Key examples, convexity preserving operations, inequalities of interest – Jensen’s

3. Convex Functions: Properties and examples, convexity preserving operations, important convex functions, quasi convex functions and approximating non-convex functions

Day 2 (4 hours)

4. Convex Optimization Problems: Unconstrained optimization, linear and quadratic forms, geometric programming, semi-definite programming, formulation of important known problems as semi-definite programs and corresponding key results

5. Constrained convex optimization: Identifying a convex problem, linear and non-linear constraints, equality and inequality constraints. Lagrange dual function, dual problem, optimality conditions (KKT).

Day 3 (4 hours)

Part II: Algorithms

1. Unconstrained minimization: descent methods, gradient descent, steepest descent, Newton’s method, and quasi-Newton and BFGS methods, implementation concerns and tricks.

2. Constrained minimization: Newton’s method with equality constraints, Infeasible start, implementation concerns

3. Interior Point Methods: Inequality constrained problems, log barrier function and central path, the barrier method, problems with generalized inequalities, primal-dual interior point methods.

4. Optimization software: MATLAB optimization toolbox and other key packages.

Day 4 (4 hours)

Part III: Real-world optimization problems with applications

1. Sparsity Constrained Optimization and Estimation

2. Covariance Estimation with structural constraints

Applications in statistics, machine learning and radar signal processing.

Schedule:

1. Day1 – 9 AM – 1 PM
2. Day2 – 9 AM-1PM
3. Day3 – 9 AM-1 PM
4. Day4 – 9 AM – 1 PM
5. Day5 – 10 AM-1 PM (final written exam)

Hours:
12 hours (3 credits)

Room:

Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa - Ground Floor

To register to the course, click here

Short Abstract:

After a general introduction on the use of the envelope-function method in the study of semiconductors, the course will focus on the application to graphene and graphene-related materials. Due to its particular lattice structure, in monolayer graphene the envelope-function equation takes the form of the Dirac-Weyl equation (i.e., the same relation that describes the behavior of relativistic massless quantum particles, which explains why in graphene several exotic relativistic effects, such as Klein tunneling, appear at non relativistic speeds). The course will describe the derivation of the Dirac envelope-function equation in graphene and related materials, the numerical methods that can be adopted for its solution, and the way in which this description can be applied for the study of transport of graphene-based devices. Particular care will be devoted to the discretization and ill-conditioning numerical problems which may emerge using this modelization and to the methods which can be used to overcome them.

Course Contents in brief:

1. General introduction to the envelope-function method in semiconductors.
2. Derivation of the Dirac envelope function equation in graphene and graphene-related materials.
3. Numerical solution of the Dirac equation and related discretization problems.
4. Application to the study of charge transport in graphene-based devices, in the presence of a generic potential profile and of an orthogonal magnetic field.

Schedule:

1. 18/07/2022: h. 14.00-18.00
2. 19/07/2022: h. 14.00-18.00
3. 20/07/2022: h. 14.00-18.00