Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

For the year 2019/2020 No calendar yet available

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

B C D F G M P Q R S V

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Castellani Umberto

umberto.castellani@univr.it +39 045 802 7988

Ceccato Mariano

mariano.ceccato@univr.it

Chiarini Andrea

andrea.chiarini@univr.it 045 802 8223

Cozza Vittoria

vittoria.cozza@univr.it

Cristani Marco

marco.cristani@univr.it +39 045 802 7841

Cubico Serena

serena.cubico@univr.it 045 802 8132

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Favretto Giuseppe

giuseppe.favretto@univr.it +39 045 802 8749 - 8748

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fummi Franco

franco.fummi@univr.it 045 802 7994

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Melzi Simone

simone.melzi@univr.it +39 045 802 7068

Muradore Riccardo

riccardo.muradore@univr.it +39 045 802 7835

Murino Vittorio

vittorio.murino@univr.it 045 802 7996

Muscolo Giovanni Gerardo

giovannigerardo.muscolo@univr.it

Pravadelli Graziano

graziano.pravadelli@univr.it +39 045 802 7081

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Quintarelli Elisa

elisa.quintarelli@univr.it +39 045 802 7852

Romeo Alessandro

alessandro.romeo@univr.it +39 045 802 7974-7936; Lab: +39 045 802 7808

Setti Francesco

francesco.setti@univr.it +39 045 802 7804

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Villa Tiziano

tiziano.villa@univr.it +39 045 802 7034

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.

Training offer to be defined

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S009004

Coordinatore

Davide Quaglia

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

II semestre dal Mar 1, 2021 al Jun 11, 2021.

Learning outcomes

The course aims to provide the knowledge necessary for the specification, modeling, development and verification of embedded network systems for industrial applications, in particular networked control systems, cyber-physical components, network infrastructures and Internet-of-Things (IoT) applications. At the end of the course the student will have to show the acquisition of the ability to analyze and understand the functioning of the networked embedded and IoT systems and the problems related to their design, implementation, verification, certification and use, with reference to their most important properties: performance, reliability, security and privacy. This knowledge will allow the student to acquire the ability to specify, model, design and verify networked embedded systems in the industrial and IoT fields, identifying the most appropriate components to integrate with each other, with the production machinery and the company information system. At the end of the course the student will be able to apply and deepen these topics independently.

Program

Theory:
- wireless embedded systems and protocols.
- networked control systems.
- protocols for smart manufacturing.
- advanced networking.

Laboratory:
- MQTT and Kafka.
- Multimedia communications and Quality of Service.
- Optimization of an actual industrial infrastructure.
- Programming of networked embedded systems

Examination Methods

Oral exam with 3 questions on theory and laboratory
Optional project:
- max 2 people
- effort: 40 hours
- possible synergy with other courses, stage, thesis
- some topics will be proposed at the end of the program but they can be proposed by students too
- max score: 3
Final score: oral exam score + project score.

Type D and Type F activities

Training offer to be defined

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Graduation

For schedules, administrative requirements and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

List of theses and work experience proposals

theses proposals Research area
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management


Area riservata studenti