2019-2020 PhD Courses

  • Course teacher: Prof. Francesco Chiti, DINFO, Unifi
  • Course title: Vehicular Networking Architectures and Technologies
  • Specially suited for Curricula:
    • Telecommunications and Telematics
  • Proposed teaching period:  First half of July 2020
  • CFU’s: 1 (4 hours)


In this Course, we provide an overview of the main aspects of VANETs from a research perspective, by giving an overview on applications trends and characterising the networks architectures and standards in a 5G comprehensive perspective.

  • Course teacher: Prof. Mara Bruzzi, Unifi
  • Course title: Material Engineering for Solar Cells
  • Specially suited for Curricula: 
    • Electronics, Electromagnetics and Electrical Systems
  • Proposed teaching period:  between July 6th and July 17th, 2020
  • CFU’s: 2 (8 hours)


Solar cell material engineering is directed to enabling the highest solar energy conversion efficiencies at low costs and with a sustainable energy balance. This course will discuss principles, concepts and materials used in solar cells. The I-V characteristics of monocrystalline, polycrystalline and amorphous silicon, nano-composites (dye-sensitized TiO2) and triple-junction solar cells will be measured and analyzed in different illumination conditions.

  • Course teacher: Prof. David Angeli, DINFO, Unifi
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
  • Proposed teaching period:  July 15,17, 2020
  • CFU’s: 1 (4 hours)



NB: this course has not yet been approved by the Doctoral Committee
  • Course teacher: Dr.  Michela Paolucci, dr.  Gianni Pantaleo, DINFO, Unifi.
  • Course title: Best Practice Network Analysis and Natural Language Processing
  • Specially suited for Curricula:
    • Computer Engineering
  • Proposed teaching period:  Preferably September-October 2020 
  • CFU’s:  3 (12 hours)


The 12-hour course (3 CFU) focuses on two main topics: Best Practice Network Analysis and Natural Language Processing. Course structure: – Concept of Best Practice Network (BPN), types of data managed and actions of users in a BPN (single users and groups of users). Methodologies and metrics of data classification and analysis in a BPN. Creation of new knowledge and concept of co-working activities. Suggestions and recommendations. Real use cases and comparison between different BPN. – Web crawling and data mining of unstructured text data: description of the main open source techniques and tools, applied to the analysis of Data coming from Social Network and Social Media. Information extraction tools from unstructured textual data, through pattern matching and Natural Language Processing (NLP) techniques: tokenizers, syntactic and moprhological analysis, Part-of-Speech tagging, syntactic parsing. Sentiment Analysis and use of open source resources (taxonomies, dictionaries) for text annotation. – Interaction between BPN and NLP: semantic analysis to provide innovative services to BPN users.

  • Course teacher: Prof. Branislav Notaros, Colorado State University
  • Course title: Higher Order Computational Electromagnetics, Uncertainty Quantification, and Meshing Techniques with Applications in Wireless Communication, Medicine, and Meteorology
  • Specially suited for Curricula:
    • Electronics, Electromagnetics and Electrical Systems
  • Proposed teaching period:  November 14th, 2019
  • CFU’s: 1 (4 hours)
  • Abstract:

Electromagnetics-related, antenna, RF, microwave, radar, microelectronics, wireless, and lightwave, technologies are exploding! The importance of computational electromagnetics (CEM) to these technologies can hardly be overstated. This seminar presents some advances in several major components of CEM, including (1) higher order method of moments, finite element method, ray-tracing, and hybrid techniques, (2) uncertainty quantification techniques for CEM modeling of RF and microwave devices and systems featuring a posteriori error estimation, sensitivity analysis, and intelligent model refinement based on adjoint methods, and (3) automatic surface meshing in CEM by the discrete surface Ricci flow method enabling generation of high quality meshes and adaptive iterative mesh refinement. The seminar also shows how these methodologies and techniques can be effectively applied to solving general real-world problems with impacts on wireless communication, medicine, and meteorology. The applications include (A) smart underground mining with an integrated wireless cyber-physical framework using CEM modeling and measurements of wireless propagation in underground mines, (B) design of RF coils for next-generation high and ultra-high field magnetic resonance imaging (MRI) scanners based on CEM and MRI experiments, and (C) accurate characterization of winter precipitation using multi-angle snowflake camera, visual hull image processing, advanced scattering methods, and polarimetric radar.

  • Course teacher: Prof. Lugi Chisci, DINFO, Unifi
  • Course title: Linear and nonlinear Kalman filtering: theory and applications
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period: January 14, 16, 21, 23 2020 from 10 to 13
  • CFU’s: 3 (12 hours)


This short course aims to provide both theoretical and practical tools to tackle estimation problems encountered in several areas of engineering and science. In particular, it is shown how to formulate such estimation problems as instances of a general dynamical system state estimation problem and how to derive the mathematical solution of the latter problem. Then it is shown that, for a linear Gaussian system, such a solution yields the well known Kalman filter. Further, approximate techniques (e.g. extended and unscented Kalman filters, particle filter, etc.) are presented for the case of nonlinear and/or non-Gaussian systems, for which an exact closed-form solution cannot be found. To conclude the theoretical part, theoretical limitations (i.e. the Cramer-Rao lower bound) on the quality of estimation are discussed. In the second part of the course, we illustrate some applications of linear/nonlinear Kalman filtering (e.g., tracking, robotic navigation, environmental data assimilation).

  • Course teacher: Prof. Marco Sciandrone, DINFO, Unifi
  • Course title: Methods for constrained optimization
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
  • Proposed teaching period:  January-February, 2020
  • CFU0s: 3 (12 hours)


The course deals with optimization methods for smooth constrained optimization. First we consider methods based on the construction of a (finite or infinite) sequence of unconstrained problems, i.e., penalty and augmented Lagrangian methods. Then, we give a short introduction on interior point methods. Finally, we analyze Sequentially Quadratic Programming methods, which can be viewed as Newton-type methods for solving constrained problems.


(ore 14.30)  “MISRA C and its key role for the compliance to
        industrial safety standards”

Embedded software plays a steadily increasing role in all industrial
sectors, and in several such sectors software is responsible for
functionality impacting the overall system safety and security.  As a
result an increasing number of companies and projects are required to
comply to industry safety standards (CENELEC EN 50128, ECSS-Q-ST-80C,
FDA “General Principles of Software Validation”, IEC 61508, IEC 62304,
ISO 26262, RTCA DO-178C). In this seminar we will focus on one of the
key aspects of such standards: this is the possibility to program in
subsets of standardized languages such as “C” or “C++”.  Starting from
an introduction to the traps and pitfalls of the “C” programming
language, we will present MISRA C, the most authoritative subset of
“C” for the development of high-integrity systems.

 (durata: 1h30’)

(ore 16.00)  “The ECLAIR software verification platform: hands-on session,
        with live examples”

ECLAIR is a powerful platform for the automatic analysis and verification
of C and C++ programs.  In this seminar we will first highlight the
main features of ECLAIR as a platform: proper integration with the
toolchain, precise tracking of the preprocessing phase, powerful
reporting capabilities and deviation mechanisms, …
ECLAIR can be instantiated over a whole range of software verification
activities, which are provided in the form of packages.  We will focus
on the following packages:

– “MISRA C:2012 + HIS Metrics”: a state-of-the-art, medium-weight
 static analyzer that almost completely automates the assessment of
 compliance with respect to MISRA C:2012 combined with a precise and
 flexible implementation of the source code metrics defined by HIS.

– “ECLAIR Bug Finder”: a very fast static analyzer for C and C++
 suitable for execution on the developer’s desktop, which is able to
 detect and report bugs and weaknesses that can lead to crashes,
 misbehaviors and security vulnerabilities.

In this session, we will demonstrate the use of ECLAIR on real
open-source software projects.

 (durata: 1h30’)

  • Course teachers: Andrea Conti (Università di Ferrara),  Stefania Bartoletti (IEIIT/CNR Bologna), Flavio Morselli (Università di Ferrara)
  • Course title: Localization-of-Things
  • Specially suited for Curricula: 
    • Control, Optimization and Complex Systems
    • Telecommunications and Telematics
  • Proposed teaching period:  January 15-30, 2020
  • CFU’s:  1 (4 hours)


The availability of real-time high-accuracy location awareness is essential for current and future wireless applications, particularly those involving Internet-of-Things and 5G communication networks. Reliable localization and navigation of people, objects, and vehicles – Localization-of-Things – is a critical component for a diverse set of applications including connected communities, smart environments, vehicle autonomy, asset tracking, medical services, military systems, and crowd sensing. The coming years will see the emergence of network localization and navigation in challenging environments with sub-meter accuracy and minimal infrastructure requirements. We will discuss the limitations of traditional positioning, and move on to the key enablers for high-accuracy location awareness. Topics covered will include: fundamental bounds, algorithms for position inference, radar signal processing, and network experimentation. Attendees of this short course will learn about location-aware networks in two ways. On the one hand, they will get a high-level overview of fundamental performance bounds, ranging techniques, positioning algorithms, sensor radar networks, and network experimentation. On the other hand, the course will serve as an introduction to the state of the art in location inference for active and passive localization employing wideband wireless technologies. Results based on measurements collected via network experimentation employing wideband and ultra-wideband radios are used to illustrate the concepts.

  • Course teacher: Prof. Marco Bertini and Lorenzo Seidenari,  Tibrio Uricchio, DINFO, Unifi
  • Course title: Introduction to Deep Learning in Keras
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period:  January – February 2020
  • CFU’s: 4 (16 hours)


Neural networks foundations: MLP, creating a simple network with Keras, towards deep learning
Keras installation and API
Deep learning with ConvNets, DCNN layers, experimenting with basic datasets, very deep networks
Generative Adversarial Networks, GANs and images

  • Course teacher: Prof. Simone Morosi, DINFO, Unifi
  • Course title: Energy Effcient Wireless Communications
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period:  January – February, 2020
  • CFU’s: 3 (12 hours)


Due to global climate change as well as economic concern of network operators, energy consumption of the infrastructure of cellular networks, or “Green Cellular Networking,” has become a popular research topic.
Particularly, the two most important reasons to pursue the development of green communications networks are the increases in carbon dioxide emissions (CO2) and in operational expenditures (OPEX). Hence, energy consumption reduction has to be dealt with in all the main activities, ICT and communications included.
While energy saving can be achieved by adopting renewable energy resources or improving design of certain hardware (e.g., power amplifier) to make it more energy-efficient, the cost of purchasing, replacing, and installing new equipment (including manpower, transportation, disruption to normal operation, as well as associated energy and direct cost) is often prohibitive. By comparison, approaches that work on the operating protocols of the system do not require changes to current network architecture, making them far less costly and easier for testing and implementation.
In this course, we first present facts and figures that highlight the importance of green mobile networking and then review existing green cellular networking research, providing general guidelines and design criteria in order to reduce power consumption, to increase the energy efficiency in cellular networks and to generalize these strategies to ICT systems. A particular focus will be on techniques that incorporate the concept of the “sleep mode” in base stations. It takes advantage of changing traffic patterns on daily or weekly basis and selectively switches some lightly loaded base stations to low energy consumption modes. As base stations are responsible for the large amount of energy consumed in cellular networks, these approaches have the potential to save a significant amount of energy.

• Motivations and scenario:
– environment and economic issues;
– impact of ICT on emissions and energy consumption;
• Summary about wired and wireless networks;
• Energy efficiency metrics;
• Mobile cellular networks:
– base station and network power consumption models;
– cell design and base station technologies;
• Green radio resource management and deployment strategies:
– traffic variation and prediction in cellular networks;
– techniques enabling sleep mode in BSs;
– BS sleep mode in 4G cellular networks;
– BS sleep mode and heterogeneous network deployment;
– Optimization techniques;
• Wireless Sensor Networks;
• 5G mobile networks:
– key enabling technologies (HetNets, massive MIMO and mmWave techniques);
– ultra-dense small cell networks;
– optimization and trade-offs of spectral and energy efficiency.

  • Course teacher: Prof. Giacomo Innocenti, DINFO, Unifi
  • Course title: Analisi di circuiti memristivi
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
    • Electronics, Electromagnetics and Electrical Systems
  • Proposed teaching period:  end January, beginning february, 2020
  • CFU’s: 1 (4 hours)


I circuiti memristivi, di cui sono state trovate realizzazioni fisiche solo nell’ultimo decennio, promettono interessanti benefici nelle applicazioni di analog computing. Il loro comportamento dinamico, però, è talmente ricco e variegato da renderne l’analisi particolarmente complicata. Il seminario si propone l’obiettivo di illustrare una recente tecnica di analisi in grado di ridurre, destrutturandola opportunamente, questa complessità.

  • Course teacher: Prof. Giovanni Collodi, Stefano Selleri, DINFO, Unifi
  • Course title: High Frequency solutions for Internet of Things connectivity
  • Specially suited for Curricula:
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
  • Proposed teaching period:  February or June
  • CFU’s: 2 (8 hours)


The course focuses on TX/RX Front Ends for Internet of Things (IoT) applications. IoT will become a pervasive technology within the next 10 years. In the course the TX/RX front end is analyzed as the central element enabling connectivity, in its parts: Antenna e Transceiver, which must be co-designed and co-optimized and cannot be considered independently in an effective design.
The course illustrates the different Transceiver and Antenna architectures, relating them to the different communication standards, highlighting their critical aspects, existing commercial solutions and illustrating possible future trends.

    • Control, Optimization and Complex Systems
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period:   to be defined
  • CFU’s:  2 (8 hours)


The objective of this course is to provide an introduction to modern spoken language processing using deep neural networks (DL). Thanks to recent advancements in DL, speech recognition is now widely present in everyday life, from voice controlled house appliances to personal assistants.
This course will briefly go over general aspects of acoustic phonetics, explain usual speech features for end-to-end DL, present basic speech processing architectures and discuss advanced automatic speech recognition and text-to-speech models along with commercial tools and potential new applications. 


– Prerequisites:
  – Some familiarity with Python and Jupyter Notebooks
  – Some background in time-domain and frequency-domain, including Fourier Transform
  – Some familiarity with deep learning (DNN, RNN) (examples probably in Tensorflow/Keras)

1h – Introduction and quick demos

1h – Guest lecture: Dr. Domingos Savio
     – (Proposed theme): Features of a beautiful voice

2h – Acoustic Phonetics
– Brief intro to human speech
– Perception and physical properties
 – fo, intensity, harmonics, formants
 – voiced and unvoiced speech
 – pitch tracking and intonation
– Basic spectrogram analysis and DFT review
– Vocoders: Griffin-Lim algorithm, Wavenet
– Sample notebooks

3h – Common speech applications and neural architectures:
    – General audio features/architectures for deep neural networks
    – Speech to text transcription
    – Text to speech
    – Keyword spotting
    – Potential applications: speaker diarization, detection of language, pathologies, anonymization, split voice from background

1h – Commercial tools and resources; wrap-up
    – Google speech transcription / MS Azure
    – Librosa / scipy stft / kapre / other tools
    – Github repos
    – Wrap-up

Baidu Deep Speech –
Tacotron 2 –
Baidu deep voice (TTS) –

  • Course teacher: Prof. Roberto Caldelli, CNIT – MICC
  • Course title: Blockchain basics
  • Specially suited for Curricula:
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period:  Second half of January 2020 or later
  • CFU’s: 1 (4 hours)


The course will provide basic issues of blockchain technologies. It will show the main concepts behind its working such as hash functions, proof of work, distributed ledger and so on.

  • Course teacher: Prof. Carlo Carobbi, DINFO, Unifi
  • Course title: Quantification of measurement uncertainty: basics, applications, trends
  • Specially suited for Curricula:
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
  • Proposed teaching period:  27-Feb-2020, morning
  • CFU’s:  1 (4 hours)


  • Course teacher: Prof. Alessandro Cidronali, DINFO, Unifi
  • Course title: Introduction to nanoelectronics for information technology
  • Specially suited for Curricula:
    • Electronics, Electromagnetics and Electrical Systems
    • Telecommunications and Telematics
    • Computer Engineering
  • Proposed teaching period:  June 16, 2020
  • CFU’s: 2 (8 hours)


The course is to be intended as the first module of a series aimed at providing the principles and the fundamental concepts nanoelectronics. It presents the key technologies, the advanced electronic materials and devices.
It is primarily aimed at PhD students of electrical engineering as well as information technology graduated looking for a broader overview.
The course discusses the present limit of conventional electron devices for computational purpose and presents the emerging technologies based on tunneling effect and low dimensional confining semiconductor structures.

  • Teaching period:  June 23-26, 2020, via Zoom (registration is required at
  • CFU’s: 1 (4 hours)


Course details
Mission and Goals
The goal of the course is to develop an understanding of the different options to realize
communication at the nanoscale among nano-precise entities, or nanomachines, being they

genetically engineered biological cells or man-made nano-devices. The specific focus will be on bio-
inspired communication through molecule exchange and biochemical reactions.

Different techniques to realize nanomachines will be surveyed in the course, with particular attention
to the tools provided by synthetic biology for the programming of biological cooperative systems.This
course will give a chance to be initiated to a very exciting cutting-edge research field, which will soon
influence many diverse research fields, such as engineering, chemistry, biology, and medicine.
The course starts with a brief overview of the field of nanoscale communications. Then it delves into
more challenging yet exciting concepts. Focus will be on modelling and designing of biological
circuits using tools available from synthetic biology.
Programme of the course
· Course Presentation.
· Overview of Molecular and Nanoscale Communication: from Motivation to Application
· Introduction to Molecular Communication Theory
· Analysis of Molecular Communication Systems
· Molecular Communicationand Biochemical Pathways
· Molecular Communication and Electrochemistry
· Design/Engineering of Molecular Communication Systems
· Molecular Communication and Neurons

· Molecular Communication and Synthetic Biology
· Towards the Internet of Bio-NanoThings

Good standing PhD students from Telecom, Electrical, Bio, Chemical, Computer, Automatic,
Physics, and Mathematical Engineering are welcome to attend this course. Most of the necessary
concepts from physics, chemistry, and biology, as well as from systems and communication
engineering, will be provided during the lectures to accommodate students with different
backgrounds, and let them benefit from a truly interdisciplinary approach. Student creativity, passion,
and open-minded attitude will be highly appreciated and rewarded.

Short Bio
Massimiliano Pierobon received his Ph.D. degree in Electrical and Computer Engineering from the
Georgia Institute of Technology, Atlanta, GA, USA, in 2013. Since August 2013, he is an Assistant

Professor with the Department of Computer Science and Engineering, University of Nebraska-
Lincoln (UNL), NE, USA, where he also holds a courtesy appointment at the Department of

Biochemistry. He is the co-Editor in Chief of Nano Communication Networks (Elsevier) since July
2017, and an Associate Editor of the IEEE Transactions on Communications since 2013. Selected
honors: 2011 Georgia Tech BWN Lab Researcher of the Year Award, 2013 IEEE
Communications Letters Exemplary Reviewer Award, UNL CSE Upper and Graduate Level
Teaching Award in 2016 and 2017, 2017 IEEE INFOCOM Best Paper Runner-up Award and Best
In-session Presentation Award. Dr. Pierobon is currently the PI of the NSF project

“WetComm: Foundations of Wet Communication Theory”, co-PI of the NSF project “Redox-
enabled Bio-Electronics for Molecular Communication and Memory (RE-BIONICS)”, and has been

the lead PIs of the NSF project “TelePathy: Telecommunication Systems Modeling and
Engineering of Cell Communication Pathways.” His research interests are in molecular
communication theory, nanonetworks, intra-body networks, communication engineering applied to
synthetic biology, and the Internet of Bio-Nano Things.

The course is organized by Prof. Lorenzo Mucchi, University of Florence, Italy.

  • Course teacher: Prof. Graziano Chesi, Univ Hong Kong
  • Course title: An introduction to SOS programming with applications in dynamical systems
  • Specially suited for Curricula:
    • Control, Optimization and Complex Systems
  • Proposed teaching period:  This course has been postponed to 2021
  • CFU’s:  2 (8 hours)


The minimization of a linear cost function subject to the condition that some matrix polynomials depending linearly on the decision variables are sums of squares of matrix polynomials (SOS) is known as SOS programming. This mini-course aims at providing a basic introduction of this class of optimization problems, with three main targets. The first target is to show that SOS programs can be cast into semidefinite programs (SDPs), which is a class of convex optimization problems where the cost function is linear and the constraints are linear matrix inequalities (LMIs). The second target is to show how SOS programs can be used for solving optimization over polynomials. The third target is to show some applications of SOS programming in the analysis of dynamical systems.

1. LMIs (2 hours)
1.1 Definitions and properties
1.2 SDP and other optimization problems with LMIs
1.3 Examples in dynamical systems
1.4 Solving optimization problems with LMIs

2. SOS polynomials (2 hours)
2.1 Definitions and properties
2.2 Gram matrix
2.3 SOS test via LMI
2.5 The case of matrix polynomials

3. SOS programming (2 hours)
3.1 Unconstrained optimization (and Hilbert’s 17th problem)
3.2 Optimization over semi-algebraic sets (and Putinar’s Positivstellensatz)
3.3 Special case: optimization over the simplex
3.4 Special case: optimization over ellipsoids

4. Applications of SOS programming in dynamical systems (2 hours)
4.1 Stability of nonlinear systems
4.2 Invariant sets of nonlinear systems
4.3 Robust stability of linear systems with time-varying uncertainties
4.4 Robust stability of linear systems with time-invariant uncertainties

Moreover, we recall that prof. Massimiliano Pieraccini will hold a course on “What is and How to write a scientific publication”. This course will be offered within the Soft and Complementary Skills courses organized by IUnifi. Proposed period: February 6th, 2020

Summer Schools

International Summer School on Ultrasonic and Piezoelectric Sensors
Department of Information Engineering , University of Florence, Italy, 22-24 July 2020

See: .

This event is organized by the Department of Information engineering, Università degli Studi di Firenze,  and the IEEE Sensors Council – Italy Chapter.

Additional PhD courses by other PhD programs

(updates and details on these courses are available on the web site of the Smart Computing PhD program

Further course opportunities

Official calendar of the PhD Program

Course offered  in the past