Hours:
24 hours (6 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 availability of an unprecedented level of computational power opens a whole new range of possibilities in several fields. This is strongly impacting the way to plan and control the motion of robots. This course will provide an approach to exploit the full potential of these new tools starting from the calculus of variations theory and then showing how to properly translate an optimal control problem into an optimization program. Hence an overview of the state-of-the-art optimization algorithms (and tools) will be given highlighting the link between different algorithms and problems. Finally examples and open problems will be discussed.

Course Contents in brief:

1. Introduction (0.5 h)
2. Elements of Calculus of Variations (3 h)
3. From Optimal Control to Optimization (3.5 h)
4. Optimization Problems (3.5 h)
5. Deterministic Optimization Algorithms (3.5 h)
6. Tools, Solvers and the Decision Tree (3.5 h)
7. Examples (3.5 h)
8. Open Problems in Motion Planning and Control of Robots (3 h)

Schedule:

Monday 25 – Friday 29 July 2022

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:

Empirical studies in software engineering provide a systematic way of evaluating theories, languages, concepts, tools or methodologies, considering the industrial context in which they are applied [1]. The course will prepare students by examining how to plan, conduct and report on empirical studies in software engineering. The course will cover all of the principal methods applicable to software engineering (controlled experiment, case studies, surveys, systematic literature reviews, and ethnography) and will describe quantitative and qualitative methods of analysis, including hypothesis testing and grounded theory. To showcase the different methods, the course will critically review representative examples of published work. At the end of the course, the students will be able to approach real-world research problems in a scientifically sound way, and contribute to theory building in software engineering research.
A previous version of this course was delivered for the MSc and Ph.D students of the University of Florence, School of Mathematical, Physical and Natural Sciences. The web version of the course has been made available on YouTube [2]. The reference book for the course is the handbook from Wohlin et al.

Course Contents in brief:

1. Overview of Empirical Methods in Software Engineering Research
2. Formulating Research Questions
3. Data Types, Measurements, Scale
4. Data Collection Techniques
5. Building Theories in Software Engineering
6. Research Strategies: the ABC Framework
7. Controlled Experiments
8. Hypothesis Testing and Statistical Tests
9. Qualitative Research Methods: Ethnography, Interviews, Grounded Theory
10. Survey Research in Software Engineering
11. Case Studies
12. Systematic Literature Reviews

Schedule:

1. 20, 22, 27, 29 September 2020 h. 9.30-12.30
2. 4, 6 October 2020 h. 9.30-12.30
3. 7 October 2020 h. 9.30-11.30

Hours:
30 hours (8 credits)

Room:

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

Aula Virtuale: click here

To register to the course, click here

Short Abstract:

In our daily lives, we often perform actions requiring fast and precise sequences of swiping and tapping movements, for example to operate with our phone. To perform this efficiently, our nervous system combines the sliding movement between the skin and the screen of the phone, the short pulse of vibrations when we click on a virtual button or swipe over a rendered texture, kinesthetic information from muscles and tendons, and efference copy of our motor command. Accessing the mechanisms underpinning the functions of the human somatosensory and motor system – which are tightly intertwined each other, can suggest useful guidelines for the design of haptic systems (interfaces and sensors) in a wide range of applications (telerobotics, rehabilitation, assistive robotics and advanced human machine interaction in Augmented and Virtual Reality) as well as for the planning and control of autonomous robots. This course will introduce the main foundations of haptics, the multi-disciplinary science that studies touch perception and the artificial sensing and delivering of tactile information through mechatronic systems, moving from the biological bases of the sense of touch and human motor system to the applications in different fields of robotics and advanced human machine interaction.

Course Contents in brief:

1. Introduction to haptics
2. Biological bases of human touch and its relationship with human motor system
3. Modelling and Psychophysics
4. Interfaces and Sensors
5. Telerobotics and virtual reality
6. Advanced human machine interaction and autonomous robotics

Schedule:

23, 24, 27, 28, 29 June 2022
h. 9.30-12-30
h. 14.30-17.30

Hours:
16 hours (4 credits)

Room:

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

Aula Virtuale: click here

To register to the course, click here

Short Abstract:

The course focuses on ultra-low power integrated circuit design for distributed and decentralized systems (e.g., IoT, AIoT), and in particular on the design of chips for edge nodes. The course provides an insight into system requirements imposed by real-world applications, the fundamentals to understand the related challenges, and advanced design ideas to address them. Several aspects are discussed from a design viewpoint, ranging from ultra-low power system architectures, architectures and circuits for processing, data sensemaking (e.g., machine learning on a chip), energy harvesting, on-chip power conversion, sensor interfaces and wireless communications.
The course is structured into three sections. In the first one, fundamentals on ultra-low power and minimum-energy design are provided as common background. Key concepts, models and techniques are presented to enable intelligent systems with divergently high peak performance and low minimum power, as relevant to current and prospective applications of distributed/decentralized systems. In the second section, recent techniques that drastically extend the performance-power scalability of intelligent systems are presented. Silicon demonstrations of better-than-voltage-scaling adaptation to the workload are illustrated for the entire signal chain from sensors to sensemaking. Demonstrations include the data and the clock path of the digital subsystem, the analog sub-system and power management. Energy-quality scaling is explored as additional dimension to break the conventional performance-energy tradeoff in error-resilient applications such as AI and vision, from networks on chip to memories and accelerators. Further performance and energy improvements are discussed through uncommonly flexible in-memory broad-purpose computing frameworks for true data locality, from buffering to signal conditioning and neural net workloads. In the third section, adaptation to an even wider range of powerperformance targets is presented to shrink and eventually suppress batteries as fundamental obstacle to overcome in the exponential scaling towards trillions of devices (environmental,
economics, logistics). Sensor interfaces, processors and wireless transceivers fitting existing infrastructure (e.g., WiFi) with power reductions by orders of magnitude are discussed and exemplified by numerous silicon demonstrations, and their system integration.
In this course, all design principles are exemplified by silicon demonstrations from the state of the art, and with extensive measurement results from our research group to closely mimic the learning experience in a lab environment. As further learning tool, databases of commercial products and state-of-the-art research prototypes are introduced and offered to the attendees to understand the trends, the requirements and the advances taking place in the field. The lecture notes are complemented by springer books available in most university libraries in electronic form to extend the learning journey beyond the course. The attendees should have some basic understanding of electronic circuits and integrated circuits and/or systems.

Course Contents in brief:

1. SECTION I: Fundamentals of ultra-low power design for intelligent self-powered systems
2. SECTION II: Design frameworks and techniques for aggressive power-performance tradeoff extension
3. SECTION III: Green and alert integrated systems without battery for environmental, technological, economic and logistic sustainability towards the trillion scale

Schedule:

1. Day1 20/06/2022 – 9:00-15:30 (6 hours): megatrends and perspectives on distributed/decentralized systems, requirements, recap of circuit models, design for nearlyminimum energy operation.
2. Day2 21/06/2022 – 9:00-15:30 (6 hours): background on power-performance tradeoff in intelligent and always-on systems, techniques to extend of power-performance range beyond voltage scaling from data path to clock path, energy-quality scaling and application to main sub-systems, in-memory computing, case studies.
3. Day3 22/06/2022 – 9:00-14:00 (4 hours): trends and need for battery suppression (environment, economics), integrated energy sources, system powering/activation schemes, battery-indifferent and battery-less system architectures, circuit techniques for main sub-systems, case studies.

Hours:
20 hours (5 credits)

Room:

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

To register to the course, click here

Short Abstract:

Cyber-Physical Systems (CPSs) are complex engineered systems, where cyber and physical components are strongly interconnected. In particular, CPSs obey both a continuous-time physical plant dynamics, and a hybrid control dynamics having both a discrete-time (event-driven) and a continuous-time component. A digital-twin is a digital prototype created to gain insight into a given system. The digital-twin is useful for system analysis, monitoring in operation, prediction of future states of the assets and prediction of their impact on damage or malfunction. This course presents enabling technologies and research challanges. The added value of a digital-twin is shown using two realistic case studies from the automotive field.

Course Contents in brief:

1. Multi-model simulation as enabling technology for digital-twins of CPSs.
2. Formal models and formal verification techniques for digital-twins.
3. Human centred digital-twins: realistic interactive prototypes of user graphical interfaces
4. A tool-chain for the development and analysis of digital-twins for CPSs. The standard “Functional Mock-up Interface” for co-simulation, and the INTO-CPS tool-chain.
5. Application of the tool-chain to two case studies from autonomous driving: 1) model predictive control for trajectory following with obstacle avoidance; 2) terrestrial vehicle platooning.

Schedule:

1. 14/09/2022: 9.00-13.00, 14.30-17.30
2. 15/09/2022: 9.00-13.00, 14.30-17.30
3. 16/09/2022: 9.00-13.00, 14.30-16.30

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:

This course introduces the basics of Radiofrequency Identification technology (RFID) from its assessed application in the logistics of goods and human-machine cooperation to the most advanced research trends in bio-engineering and in predictive maintenance. Indeed, an RFID system is one of the best scalable infrastructures that can handle a single device, like an implanted sensor and a fruit, but it can, however, be indefinitely replicated to control a multitude of entities in farms and even in process of huge complexity thus becoming an unprecedented source of big-data.
The course will show how low-cost RFID devices, originally devoted to the identification as barcode evolution, can be used as sensors of temperature, humidity, gases, deformations, motion, and can be therefore combined with the emerging epidermal electronics and new bio-compatible materials. The integration of the above components is described to provide sensorized second skins and a new generation of empowered implanted prostheses (orthopedic, cardiovascular and dental) with self-diagnostic capability without using any battery. The related physical security and privacy issues will be also analyzed.
Finally, possible applications to the manufacturing factories are discussed to enable predictive analysis and the management of huge-scale processes like a pandemic emergency.
The theoretical lessons will be complemented by laboratory demonstrations and training.

Course Contents in brief:

1. Basics on Radiofrequency Identifications (RFID)
2. RFID for sensing
3. Epidermal and implantable RFID devices
4. Security and Privacy of RFID framework
5. Applications to IoT systems: wearable devices for the human-machine interaction, predictive maintenance, food ripening, precision medicine, pandemics
6. Laboratory demonstration and training

Schedule:

1. 14/06/2022: 14:00-18:00
2. 15/06/2022: 9:30-12:30, 14.00 -17.00
3. 16/06/2022: 9:30-12:30, 14.00 -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:

Since a couple of years, space flight is again developing strongly including several successful mis-sions to Mars. The next big goal is to send humans again to Moon and establish the Deep Space Gateway, which is seen as the prerequisite for manned missions to Mars that are also already un-der investigation. Additive Manufacturing (AM) technologies do play an important role nowadays in fabrication of parts for spaceships and extraterrestrial vehicles and it is generally accepted that 3D printers will be used in space in near future for the production of spare parts. Other research is focussed on utilising autonomous AM robots for building protective housings on Moon (or later Mars) prior to the arrival of first astronauts.
Also 3D bioprinting, which is defined as AM with live cells is under intense investigation for appli-cations in space. The European Space Agency (ESA) has decided to install a bioprinter in the ESA Biolab at ISS, which shall become functional in 2025. Primarily, such devices shall be utilised for the on-site fabrication of three-dimensional tissue models that can be used for exploration of the effects of space conditions like microgravity and radiation on organised human tissues and 3D cell constructs. In the long-term, bioprinting might become a powerful tool for the generation of tis-sues for medical treatments of injured or ill astronauts in the upcoming far-distant, manned space missions. The doctoral course shall give an overview of these fascinating developments.

Course Contents in brief:

1. Topic 1: Additive Manufacturing (AM) and respective materials relevant in space flight
2. Topic 2: AM of housings on the Mon using locally available materials
3. Topic 3: 3D bioprinting technologies for the fabrication of living tissue models
4. Topic 4: Proposed utilisation of bioprinting in manned space missions

Schedule:

1. Day 1 – 11:00-12:00, 13:00-17:30
2. Day 2 – 9:00-12:00, 13:00-15:30
3. Day 3 – 9:00-12:00, 13:00-15:00

Hours:
12 hours (3 credits)

Room:

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

To register to the course, click here

Short Abstract:

Imagine that, few years from now, someone announces that a large-scale quantum computer has been successfully built. The next day, the New York Times claims that all the encrypted communications on the Internet are broken, and public opinion breaks into panic. Post-Quantum Cryptography (PQC) includes all those cryptosystems that are believed to be resistant against attacks by both classical computers and quantum computers. PQC is paramount to avoid the catastrophic scenario said before.
In this PhD course we will introduce the most promising family of PQC, namely Lattice-Based Cryptography.

Course Contents in brief:

1. Introduction to Post-Quantum Cryptography (Grover’s algorithm, Shor’s algorithm, PQC families)
2. Lattice problems (SVP)
3. Lattice-based hashes (Ajtai’s construction)
4. Lattice-based encryption schemes (Goldreich-Goldwasser-Halevi scheme, NTRU scheme)
5. LWE-based encryption schemes

Schedule:

1. Day1 - 3 hours - 10:30 - 13:30
2. Day2 - 3 hours - 10:30 - 13:30
3. Day3 - 3 hours - 10:30 - 13:30
4. Day4 - 3 hours - 10:30 - 13:30 (including final exam)

Hours:
24 hours (6 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:

Computer Aided Design (CAD) software facilitates the creation of 3D models, which can be the starting geometry for running a finite element analysis or directly fabricating a part with additive manufacturing (AM) technologies. An effective design takes into account multiples aspects, such as materials properties and the fabrication technologies, which have to be considered since the drawing phase. In particular, AM technologies have reduced both the design constrains and the prototyping costs, becoming an enabling tool for many engineering areas.
Indeed, the Course aims at providing Information Engineers with fundamentals of computer aided design optimized for AM, through frontal lessons and practical CAD sessions.

Course Contents in brief:

1. Fundamentals of AM technologies (4h)
2. The role of engineering drawing; from manual sketch and to computer aided design (CAD) (4h)
3. Use of CAD software: part design and assembling (8h)
4. Design for Fused Deposition Modelling (theory and practice) (4h)
5. Design for Stereolithography (theory and practice) (4h)

Schedule:

6 lessons (4 hours each)

1. July 4th 2022, 14:30 - 18:30
2. July 6th 2022, 14:30 - 18:30
3. July 8th 2022, 14:30 - 18:30
4. July 11th 2022, 14:30 - 18:30
5. July 13th 2022, 14:30 - 18:30
6. July 15th 2022, 14:30 - 18:30

Hours:
24 hours (6 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 years, information communication, computation and storage technologies are jointly reshaping the way we use technology, meeting the future needs of a wide range of big data and artificial intelligence applications and, paving the way for a full-customized autonomous user experience. In 2020 the 5G -Next Generation Communication Networks is expected to be operational and a global game changer from a technological, economic, societal and environmental perspective. 5G industry is intensively working today on designing, prototyping and testing fundamental technological advances to de-liver the promised performance in terms of latency, energy efficiency, wireless broadband capacity, elasticity, etc. Nevertheless, many experts say that the next big step for cellular networks is not 5G, it is the distributed support of the cloud and AI.
This set of lectures will cover the vision, the use cases, the architecture design and technical tools for understanding the key enabling technologies that will enable beyond 5G networks to meet its challenging performance targets and how ‘the cloud’ will play an operational role in future wireless networks. The lecture will also introduce and detail very innovative concepts freshly under investigation for future B5G/6G networks such as Reconfigurable Intelligent surfaces and the integration of non-terrestrial communication and edge intelligence with terrestrial communication systems. Moreover, dedicated lectures will promotes the idea that including semantic and goal-oriented aspects in future 6G networks can produce a significant leap forward in terms of system effectiveness and sustainability. Semantic communication goes beyond the common Shannon paradigm of guaranteeing the correct reception of each single transmitted packet, irrespective of the meaning conveyed by the packet. The idea is that, whenever communication occurs to convey meaning or to accomplish a goal, what really matters is the impact that the correct reception/interpretation of a packet is going to have on the goal accomplishment. Focusing on semantic and goal-oriented aspects and, possibly combining them, helps to identify the relevant information, i.e. the information strictly necessary to recover the meaning intended by the transmitter or to accomplish a goal. Combining knowledge representation and reasoning tools with machine learning algorithms paves the way to build semantic learning strategies enabling current machine learning algorithms to achieve better interpretation capabilities and contrast
adversarial attacks. 6G semantic networks can bring semantic learning mechanisms at the edge of the network and, at the same time, semantic learning can help 6G networks to improve their efficiency and sustainability.
The lecture will offer a flora for interactive discussions on future research axes and open challenges on B5G/6G networks.

Course Contents in brief:

1. Lecture 1 (3h) - Introduction to evolution of Wireless Networks from 3G+ to 5G. Details on technologies enabling the revolution between 4G and 5G networks.
2. Lecture 2 (1.5h) – 6G, The next frontier: Visions, roadmaps, opportunities, issues, HW reality check
3. Lecture 3 (3h) – The quest for high spectrum bands: mmW, sub-THz and VLC communications. Issues and practical examples.
4. Lecture 4 (3h) – From the Mobile Edge Computing paradigm to network cloudification and Edge AI
5. Lecture 5 (1.5h) – Sustainable and energy efficient 6G Connect-Compute-Control Networks
6. Lecture 6 (1.5h) - 6G: The reconfigurable Intelligent Surfaces Opportunities for shaping the Environment as a Service. The RISE-6G case.
7. Lecture 7 (1.5h) - 6G: The non-terrestrial Communication integration and the on demand intelligent support for 3-dimensional services. The 5G-Allstar case.
8. Lecture 7 (3h) – Challenges in AI & Wireless Communications for 6G
9. Lecture 8 (3h) - 6G: The Semantic Communication opportunity and recent research results.
10. Lecture 9 (1.5h) - the Goal-Oriented Communications opportunity and recent research results.
11. Lecture 10 (1.5h) A strategy for future 6G research axes. Open discussions.

Schedule:

1. 18/07/2022 ore 9:00-13:00 (4 ore)
2. 19/07/2022 ore 9:00-13:00 (4 ore)
3. 20/07/2022 ore 9:00-13:00 (4 ore)
4. 21/07/2022 ore 9:00-13:00 e 15:00-17:00 (6 ore)
5. 22/07/2022 ore 9:00-13:00 e 15:00-17:00 (6 ore)