Hours:
24 hours (6 credits)

Room:
From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

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 27 – Friday 31 July 2020

ATTENZIONE!

Si informano tutti gli interessati che il Corso del Dr. Gianpaolo Coro è stato annullato.

Hours:
20 hours (5 credits)

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

Short Abstract:
Big Data analytics is gaining large interest in both public and scientific agendas, because it allows to extract valid information from a large amount of noisy data and to produce valuable information for decision makers. Applications of Big Data analytics can be found in a large variety of domains, including economics, physics, healthcare, and biology. For example, analytics has been used in biology to predict the impact of climate change on species’ distribution, to monitor the effect of overfishing on economy and marine biodiversity, and to prevent ecosystems collapse.
In this course, practical applications of Big Data analytics will be shown, with focus on several signal processing and machine learning-based techniques. The course will clarify the general concepts behind these techniques, with an educational approach making these concepts accessible also to students with intermediate mathematical skills. The examples will regard real cases involving data that would have been hardly human-analyzed and corrected, especially in the domain of biology. The explained techniques will include: automatic periodicities detection, time series forecasting, Artificial Neural Networks, Support Vector Machines, Maximum Entropy, Markov Chains Monte Carlo, geographical maps comparison, global scale species distributions, species invasion prediction.
The above techniques have a general purpose applicability and the students will be able to use them in other domains too. Cloud computing, data sharing, experiments reproducibility, usage of data representation standards and most of the requirements of Big Data analytics systems will be explained and practiced in the context of the new Open Science paradigm. In order to practice with the experiments, the students will use a distributed e-Infrastructure (D4Science) developed at ISTI-CNR and used in a number of international projects. This Web-based platform hides the complexity of implementing Big Data analytics processes from scratch and allows students to concentrate on experiments configuration, results evaluation, and models’ behaviour understanding. For this reason, the course does not require any programming skill and is suited for students in Computer Engineering, Informatics, Telecommunications engineering, Mathematics, Statistics, and Computational Biology.

Course Contents in brief:

• Distributed computing
• Big Data analytics
• e-Infrastructures
• Time series forecasting and periodicities detection
• Machine Learning-based methods
• GIS maps

Schedule:

Corso ANNULLATO

14-18 September 2020

• Day1 – e-Infrastructures, Cloud and Distributed computing– 9.00 – 13.00
• Day2 – Dimensionality reduction – 9.00 – 13.00
• Day3 – Time series analysis and applications – 9.00 – 13.00
• Day4 – Machine learning-based modelling and applications – 9.00 – 13.00
  Day5 – Tools for Open Science – 9.00 – 13.00

Hours:
16 hours (4 credits)

Room:

From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

To register to the course, click here

Short Abstract:
This course deals with the electrical and thermal transport at the nanoscale. The principles of nanofabrication and of the main nanotechnological processes are also covered by this course[1,2]. Techniques for the characterization of the transport at the nanoscale level, both electrical and thermal, will be illustrated and discussed.
The potentialities for nanodevices for thermoelectric conversion will be enlightened.
Finally, the main applications in the fields of energy scavengin and green energy harvesting of thermoelectric generators, based on nanostructured silicon, will be illustrated. Particular focusing will be given to the powering of sensor nodes for IoT and for Industy 4.0 applications.

Course Contents in brief:

• Nanotechnology and Nanofabrication
• Electrical and thermal transport: theory
• Thermoelectric characterization
• nanostructured thermoelectric generators for energy scavenging/energy harvesting.
  

Schedule:

• Day1 – 9:00 - 13:00. Electrical and thermal transport in nanodevices: principles of thermoelectric conversion.
• Day2 – 9:00 - 13:00. Main techniques for the fabrication of nanodevices based on silicon nanowires and nanostructures. Techniques for the thermal and electrical characterization at the nanoscale.
• Day3 – 9:00 - 13:00. Energy scavenging and gree energy harvesting applications of nanostructured thermoelectric generator, with emphasis to the powering of Iot and of systems for Industry 4.0.
• Day4 – 9:00 - 13:00. Energy scavenging and gree energy harvesting applications of nanostructured thermoelectric generator, with emphasis to the powering of Iot and of systems for Industry 4.0.

Hours:
16 hours (4 credits)

Room:
From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

To register to the course, click here

Short Abstract:
The course covers the most important resource allocation algorithms for multicarrier radio systems with the goal to illustrate the main techniques and show what are the leading mathematical tools employed to solve the allocation problems.

Course Contents in brief:

Depending on the technical skills of the audience the structure of the course could slightly change its organization. A tentative syllabus is the following:

1. Introduction to multicarrier systems and convex optimization.
2. Single-user allocation.
3. Orthogonal multi-user allocation.
4. Muti-user allocation with interference.
   • Resource allocation for MIMO systems: broadcast and interference channel.
   • Resource allocation algorithms for D2D, FD and NOMA systems.
5. Multi-cell allocation: static and dynamic algorithms. Distributed and centralized algorithms.

Schedule:

• Day 1 - 15 June 2020 - 14:00 – 18:00,
• Day 2 - 16 June 2020 - 14:00 – 18:00,
• Day 3 - 17 June 2020 - 14:00 - 18:00,
• Day 4 - 18 June 2020 - 14:00 - 18:00.

Hours:
20 hours (5 credits)

Room:
From remote by using Microsoft Teams. The link will be sent in due time to all students who registered to the seminar.

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 cloud. This lecture will cover both architecture and detail technical tools for understanding the key enabling technologies that will enable 5G networks to meet its challenging performance targets and how ‘the cloud’ will play an operational role in future wireless networks.

Course Contents in brief:

1. Introduction to evolution of Wireless Networks from 3G+ to 5G. Details on technologies enabling the revolution between 4G and 5G networks.
2. Network densification, resource management and heterogeneous networks
3. Advanced interference management techniques from heuristics to information theory
4. Millimeter waves, Massive MIMO and antenna design Energy efficiency and its advanced techniques
5. The ‘cloudification’ of 5G: from central-RAN to mobile edge cloud. Details examples of convex optimization tools and millimeter wave spectrum use
6. Energy efficiency and its advanced techniques
7. 6G the next frontier of research: Vision, roadmaps, enabling technologies.

Schedule:

Hours:
24 hours (6 credits)

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

Short Abstract:
Bioprinting is an inherently cross-disciplinary scientific field that focuses on computer aided processes for manufacturing biomedically relevant products. These processes lead to products that may involve living (cells and/or tissues) and nonliving (bio-supportive proteins, scaffolds) components. The course introduces students to cell printing, patterning, assembling, 3D scaffold fabrication, cell/tissue-on-chips as a coherent micro-/nano-fabrication toolkit. Real-world examples illustrate how to apply bioprinting techniques in areas such as regenerative medicine, pharmaceuticals and tissue engineering

Course Contents in brief:

• In Vitro Bioprinting of Tissues and Organs (3h)
• Biomaterials for Biofabrication of 3D Tissue Scaffolds (3h)
• Fabrication of Microscale Hydrogels for Tissue Engineering Applications (3h)
• Polymeric Membranes for the construction of Tissues and Organs (3h)
• Laser-Assisted and other Bioprinting tools for Tissue Engineering (3h)
• Modular Tissue Engineering (3h)
• Formation of Multicellular Microtissues and Applications in Bioprinting (3h)
• Breast Reconstruction Using Biofabrication-Based Tissue Engineering Strategies (3h)

Schedule:

• Wednesday 29th January, 14:30 – 17:30
• Friday 31th January, 14:30 – 17:30
• Wednesday 5th February, 14:30 – 17:30
• Friday 7th February, 14:30 – 17:30
• Wednesday 12th February, 14:30 – 17:30
• Friday 14th February, 14:30 – 17:30
• Wednesday 19th February, 14:30 – 17:30
• Friday 21st February, 14:30 – 17:30

Hours:
16-18 hours (4 credits)

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

Short Abstract:
During the last two decades, electronics industry has seen many commercial versions of electrical double layer capacitors (EDLC), which are also known as ultra-capacitors and supercapacitors (SC), with the aim of complementing or replacing electrochemical batteries. EDLCs come in single-cell capacitance values from 0.2 to 7500 farads, with the limitation of very low DC voltage ratings from 0.7 V to 4 V. A general observation is that for the same device volume of an electrolytic capacitor, an EDLC gives an approximately one million times larger capacitance as pictorially shown below. Recently some SC manufacturers have introduced a novel family of ‘supercap-batteries’ where capacitance has gone up to 70,000 F. Compared to conventional capacitors with large DC voltage ratings, EDLCs offer one to two order greater energy density and approximately twice the power density. Based on these facts, supercapacitors can be used for unique and novel circuit topologies to achieve: significantly high energy efficiency in DC-DC converters; surge protection; rapid energy transfer; loss minimised sub modular inverters and renewable energy converters with DC-UPS capability.

Seminar will present an in-depth discussion on how to develop unique solutions to well-known issues in power electronics with examples of developing many patented or patent pending SC assisted (SCA) techniques such as SCA low dropout regulator (SCALDO), SCA surge absorber (SCASA), SCA temperature modification apparatus (SCATMA), SCA Sub modular inverter (SCASMI) and SCA light emitting diodes (SCALED). Industrial applications of these SCA techniques will be

Course Contents in brief:

1. Capacitors and their limits
   • Capacitor fundamentals
   • Capacitor types and their properties
   • Capacitors’ application scope and limits
   • Electrolytic capacitors vs Supercapacitors
2. Energy storage device families and Ragone plot
   • Energy storage in electrical systems
   • Compressed air energy storage
   • Superconductive magnetic energy storage
   • Rapid energy transfer requirements and fundamental circuit issues
   • Technical specifications of energy storage device
   • Ragone plot
   • Types, construction and characteristics of EDLCs, hybrid devices and capa-batteriesHistorical background
   • Electrical double-layer effect and device construction
   • Pseudocapacitance and pseudocapacitors
   • Hybridization of electrochemical capacitors and rechargeable batteries
   • Modelling and equivalent circuits
   • Testing of devices and characterization
   • Modules and voltage balancing
   • Capa-batteries
3. Traditional applications of EDLCs
   • Automotive and transportation applications
   • Power quality applications
   • Portable products
   • Theoretical framework for non-traditional Supercapacitor assisted (SCA) circuit topologiesReview of the simple RC circuit loop theory
   • Modification of the traditional RC circuit, by an over-rated DC source, and a pre-charged exponentially large capacitor
   • Inserting a useful load into the loop with a supercapacitor
   • SCA low dropout regulator (SCALDO) technique for high efficiency linear DC-DC convertersDC-DC converters and DC power management
   • Supercapacitor assisted low dropout regulator (SCALDO) technique
   • SCALDO implementation examples
   • Comparison between SCALDO regulators and charge pumps
4. SCA surge absorber technique and an example of a commercial application
   • Lightning and inductive energy dumps in electric circuits and typical surge absorber techniques
   • Supercapacitor as a surge absorption device: summarized results of a preliminary investigation
   • Design approaches to a supercapacitor-based surge protector
   • SCA temperature modification apparatus (SCATMA) for rapid heating of fluids
   • Problem of traditional heating from direct AC mains supply and heating system specifications
   • Commercial solutions for eliminating water wastage due to storage in buried plumbing
   • SC-based solution with pre-stored energy
   • Results from an ongoing prototype development exercise
5. SCA sub modular inverter (SCASMI) for renewable energy applications
   • Reduced losses and efficiency advantage in inverter design
   • Basic principle of SCASMI technique
   • Generalised principle and operating modes
   • Implementation details of SCASMI inverters
6. SCA light emitting diodes (SCALED) technique for DC Microgrid applications
   • DC operation of LED units – 12 V and higher voltage DC operable flood lighting units
   • Supercapacitors for short term Dc-UPS capability to overcome solar energy fluctuations
   • Replacing battery banks with supercapacitors – issue of MPPT implementation
   • SCALED topology and its theory related to high efficiency LED lighting
   • An overview of a pilot project at Ports of Auckland Jetty area

 Schedule:

• Day1 – 9:00 – 12:00, 13:30- 16:30
• Day2 – 9:00 – 12:00, 13:30- 16:30
• Day3 – 9:00 – 13:00

Hours:
20 hours (5 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Largo L. Lazzarino 1, 56122 Pisa, Edificio A, piano 6

Short Abstract:
Machine Vision and Augmented Reality are currently hot topics given the possible applications in many fields. This course gives a theoretical and practical introduction of these topics taking into account optical, geometrical, algebraic, SW, HW, and human factors aspects.

Course Contents in brief:

1. Course introduction and possible applications
2. Camera models and principles of geometric optics
3. Geometric and algebraic pinhole model of common cameras
4. Element of rigid transformations
5. Zhang method to determine the pinhole camera parameters
6. Tracking with single and multiple camera systems
7. 3D surface reconstruction with single and multiple camera systems
8. Basic principles of Virtual Reality and main HW&SW components
9. Augmented Reality definition and main HW&SW components
10. How to obtain the registration in VST systems
11. Challenges in OST systems

Schedule:

Hours:
8 hours (2 credits)

Room:
Aula ADII1, Largo Lucio Lazzarino 1, Pisa
e
Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
We live in a time of automated information warfare, where hordes of bots (automated software programs) rampage in our online social ecosystems. These content-polluting bots are employed by both malicious actors aiming to spread misinformation, as well as by traditional news outlets fighting for readers’ attention.
In this course, we introduce and we experiment with the fundamentals of social media crawling and analysis, we discuss the issues related to information credibility in social media, and we investigate the role of social bots in the spread of high- and low-quality (e.g., fake news) information. We also introduce the task and the challenges of social bot detection. Then, we report on social media platforms capabilities of detecting bots, and on human performance in discriminating between legitimate and bot accounts. Finally, we thoroughly discuss different machine learning and AI approaches to the automatic detection of social bots (e.g., network-, content-, and behavior-based), highlighting those that currently represent the most promising ones. The course also includes hands-on sessions in Python, where participants will write scripts for collecting live data from Twitter and will learn to perform bot detection. The course also covers points such as available datasets, software, and APIs for supporting the study of information credibility and the detection of social bots.

Course Contents in brief:

• Social media and information credibility (e.g., fake news, coordinated inauthentic behavior);
• Social bots and their role in the spread of low-quality information;
• Early (i.e., supervised) and recent (i.e., unsupervised, group-based) machine learning/AI approaches to the detection of social bots;
• A look into the future of information credibility and social bot detection;
• Data collection from Twitter and bot detection experiments in Python.

Schedule:

• 28 April 2020 - 13:30-15:30 - Aula ADII1, Largo Lucio Lazzarino
• 29 April 2020 - 13:30-16:30 - Aula ADII1, Largo Lucio Lazzarino
• 30 April 2020 - 10:30-13:30 - Aula Riunioni Dip., Via G. Caruso 16, Pisa – Ground Floor

Hours:
18 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 series of lectures will cover High-Performance Computing (HPC) architectures and provide a systems hardware perspective. The lectures revolve around three axes: the processing elements, the memory system and the interconnection networks at the system level. The lectures will present high-performance out-of-order processors, vector processors and GPUs, high performance memory systems (e.g. HBM, HMC) and interconnection network architectures.
The course will have a 1h discussion introduced by Sergio Saponara, University of Pisa, and Vassilis Papaefstathiou, FORTH, regarding the dissemination to PhD community of the global vision of the H2020 European Processor Initiative (EPI), part of the EuroHPC JU roadmap, involving 27 European partners (including FORTH and University of Pisa)

Course Contents in brief:

• Introduction to EPI and HPC (3h)
• High-Performance Processors: Out-of-Order CPUs, Vector, GPU (6h)
• Memory Systems for HPC (4.5 h)
• Interconnection Network Architectures for HPC (4.5 h)

Schedule: