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..

Academic year:
Definition of lesson periods
Period From To
Primo semestre Oct 4, 2021 Jan 28, 2022
Secondo semestre Mar 7, 2022 Jun 10, 2022
Exam sessions
Session From To
Sessione invernale d'esame Jan 31, 2022 Mar 4, 2022
Sessione estiva d'esame Jun 13, 2022 Jul 29, 2022
Sessione autunnale d'esame Sep 1, 2022 Sep 30, 2022
Degree sessions
Session From To
Sessione Estiva Jul 15, 2022 Jul 15, 2022
Sessione Autunnale Oct 14, 2022 Oct 14, 2022
Sessione Invernale Mar 14, 2023 Mar 14, 2023
Holidays
Period From To
Festa di Tutti i Santi Nov 1, 2021 Nov 1, 2021
Festa dell'Immacolata Concezione Dec 8, 2021 Dec 8, 2021
Festività natalizie Dec 24, 2021 Jan 2, 2022
Festa dell'Epifania Jan 6, 2022 Jan 7, 2022
Festività pasquali Apr 15, 2022 Apr 19, 2022
Festa della Liberazione Apr 25, 2022 Apr 25, 2022
Festività Santo Patrono di Verona May 21, 2022 May 21, 2022
Festa della Repubblica Jun 2, 2022 Jun 2, 2022
Chiusura estiva Aug 15, 2022 Aug 20, 2022

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 Enrollment FAQs

Academic staff

B C D E F G M P Q R S T V Z

Belussi Alberto

symbol email alberto.belussi@univr.it symbol phone-number +39 045 802 7980

Bombieri Nicola

symbol email nicola.bombieri@univr.it symbol phone-number +39 045 802 7094

Calanca Andrea

symbol email andrea.calanca@univr.it symbol phone-number +39 045 802 7847

Castellani Umberto

symbol email umberto.castellani@univr.it symbol phone-number +39 045 802 7988

Ceccato Mariano

symbol email mariano.ceccato@univr.it

Combi Carlo

symbol email carlo.combi@univr.it symbol phone-number +39 045 802 7985

Cristani Marco

symbol email marco.cristani@univr.it symbol phone-number +39 045 802 7841

Cubico Serena

symbol email serena.cubico@univr.it symbol phone-number 045 802 8132

Dall'Alba Diego

symbol email diego.dallalba@univr.it symbol phone-number +39 045 802 7074

Enrichi Francesco

symbol email francesco.enrichi@univr.it symbol phone-number +390458027051

Farinelli Alessandro

symbol email alessandro.farinelli@univr.it symbol phone-number +39 045 802 7842

Fiorini Paolo

symbol email paolo.fiorini@univr.it symbol phone-number 045 802 7963

Fummi Franco

symbol email franco.fummi@univr.it symbol phone-number 045 802 7994

Giachetti Andrea

symbol email andrea.giachetti@univr.it symbol phone-number +39 045 8027998

Giacobazzi Roberto

symbol email roberto.giacobazzi@univr.it symbol phone-number +39 045 802 7995

Gialanella Stefano

symbol email stefano.gialanella@unitn.it symbol phone-number 0461 282420

Maris Bogdan Mihai

symbol email bogdan.maris@univr.it symbol phone-number +39 045 802 7074

Meli Daniele

symbol email daniele.meli@univr.it symbol phone-number +39 045 802 7908

Menegaz Gloria

symbol email gloria.menegaz@univr.it symbol phone-number +39 045 802 7024

Muradore Riccardo

symbol email riccardo.muradore@univr.it symbol phone-number +39 045 802 7835

Murino Vittorio

symbol email vittorio.murino@univr.it symbol phone-number +39 045 802 7996

Muscolo Giovanni Gerardo

symbol email giovannigerardo.muscolo@univr.it

Pianezzi Daniela

symbol email daniela.pianezzi@univr.it

Pravadelli Graziano

symbol email graziano.pravadelli@univr.it symbol phone-number +39 045 802 7081

Quaglia Davide

symbol email davide.quaglia@univr.it symbol phone-number +39 045 802 7811

Quintarelli Elisa

symbol email elisa.quintarelli@univr.it symbol phone-number +39 045 802 7852

Rizzi Romeo

symbol email romeo.rizzi@univr.it symbol phone-number +39 045 802 7088

Romeo Alessandro

symbol email alessandro.romeo@univr.it symbol phone-number +39 045 802 7936; Lab: +39 045 802 7808

Setti Francesco

symbol email francesco.setti@univr.it symbol phone-number +39 045 802 7804

Tomazzoli Claudio

symbol email claudio.tomazzoli@univr.it

Toniolo Sara

symbol email sara.toniolo@univr.it symbol phone-number 045 802 8683

Villa Tiziano

symbol email tiziano.villa@univr.it symbol phone-number +39 045 802 7034

Zavatteri Matteo

symbol email matteo.zavatteri@univr.it symbol phone-number +39 045 802 7814

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 enrollment year.

1° Year

ModulesCreditsTAFSSD
9
B
ING-INF/04
Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory activities for Smart Systems & Data Analytics
6
B/C
INF/01 ,ING-INF/06
6
B/C
ING-INF/05

2° Year  activated in the A.Y. 2022/2023

ModulesCreditsTAFSSD
Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
Compulsory activities for Smart Systems & Data Analytics
6
B/C
ING-INF/05
Final exam
24
E
-
ModulesCreditsTAFSSD
9
B
ING-INF/04
Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory activities for Smart Systems & Data Analytics
6
B/C
INF/01 ,ING-INF/06
6
B/C
ING-INF/05
activated in the A.Y. 2022/2023
ModulesCreditsTAFSSD
Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
Compulsory activities for Smart Systems & Data Analytics
6
B/C
ING-INF/05
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
Between the years: 1°- 2°
Further activities
3
F
-
Between the years: 1°- 2°
Training
3
F
-

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

Type D and Type F activities

Le attività formative di tipologia D sono a scelta dello studente, quelle di tipologia F sono ulteriori conoscenze utili all’inserimento nel mondo del lavoro (tirocini, competenze trasversali, project works, ecc.). In base al Regolamento Didattico del Corso, alcune attività possono essere scelte e inserite autonomamente a libretto, altre devono essere approvate da apposita commissione per verificarne la coerenza con il piano di studio. Le attività formative di tipologia D o F possono essere ricoperte dalle seguenti attività.

1. Insegnamenti impartiti presso l'Università di Verona

Comprendono gli insegnamenti sotto riportati e/o nel Catalogo degli insegnamenti (che può essere filtrato anche per lingua di erogazione tramite la Ricerca avanzata).

Modalità di inserimento a libretto: se l'insegnamento è compreso tra quelli sottoelencati, lo studente può inserirlo autonomamente durante il periodo in cui il piano di studi è aperto; in caso contrario, lo studente deve fare richiesta alla Segreteria, inviando a carriere.scienze@ateneo.univr.it il modulo nel periodo indicato.

2. Attestato o equipollenza linguistica CLA

Oltre a quelle richieste dal piano di studi, per gli immatricolati dall'A.A. 2021/2022 vengono riconosciute:

  • Lingua inglese: vengono riconosciuti 3 CFU per ogni livello di competenza superiore a quello richiesto dal corso di studio (se non già riconosciuto nel ciclo di studi precedente).
  • Altre lingue e italiano per stranieri: vengono riconosciuti 3 CFU per ogni livello di competenza a partire da A2 (se non già riconosciuto nel ciclo di studi precedente).

Tali cfu saranno riconosciuti, fino ad un massimo di 6 cfu complessivi, di tipologia F se il piano didattico lo consente, oppure di tipologia D. Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

Gli immatricolati fino all'A.A. 2020/2021 devono consultare le informazioni che si trovano qui.

Modalità di inserimento a librettorichiedere l’attestato o l'equipollenza al CLA e inviarlo alla Segreteria Studenti - Carriere per l’inserimento dell’esame in carriera, tramite mail: carriere.scienze@ateneo.univr.it

3. Competenze trasversali

Scopri i percorsi formativi promossi dal TALC - Teaching and learning center dell'Ateneo, destinati agli studenti regolarmente iscritti all'anno accademico di erogazione del corso https://talc.univr.it/it/competenze-trasversali

Modalità di inserimento a libretto: non è previsto l'inserimento dell'insegnamento nel piano di studi. Solo in seguito all'ottenimento dell'Open Badge verranno automaticamente convalidati i CFU a libretto. La registrazione dei CFU in carriera non è istantanea, ma ci saranno da attendere dei tempi tecnici.  

4. Periodo di stage/tirocinio

Oltre ai CFU previsti dal piano di studi (verificare attentamente quanto indicato sul Regolamento Didattico): qui informazioni su come attivare lo stage. 

Verificare nel regolamento quali attività possono essere di tipologia D e quali di tipologia F.

Insegnamenti e altre attività che si possono inserire autonomamente a libretto

 

Academic year:
Primo semestre From 10/4/21 To 1/28/22
years Modules TAF Teacher
1° 2° Data Analysis for Biomedical Sciences D Gloria Menegaz (Coordinator)
1° 2° Introduction to Robotics for students of scientific courses. D Paolo Fiorini (Coordinator)
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinator)
Secondo semestre From 3/7/22 To 6/10/22
years Modules TAF Teacher
1° 2° Introduction to Robotics for students of scientific courses. D Paolo Fiorini (Coordinator)
1° 2° Introduction to 3D printing D Franco Fummi (Coordinator)
1° 2° HW components design on FPGA D Franco Fummi (Coordinator)
1° 2° Rapid prototyping on Arduino D Franco Fummi (Coordinator)
1° 2° Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinator)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Python programming language D Giulio Mazzi (Coordinator)

Teaching code

4S009004

Credits

6

Coordinator

Davide Quaglia

Language

English en

Also offered in courses:

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

The teaching is organized as follows:

IoT Systems

Credits

3

Period

Semester 2

Academic staff

Davide Quaglia

Networked embedded systems

Credits

3

Period

Semester 2

Academic staff

Davide Quaglia

Learning objectives

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.

Prerequisites and basic notions

Knowledge of the fundamental concepts of communication networks and of the protocols of the TCP/IP architecture. Programming in C, Python and Java also via command line interface. Ability to use the UNIX shell.

Program

Theory:
- Wireless embedded systems and protocols.
- Networked control systems.
- Network architectures for smart manufacturing.
- Advanced networking.
Laboratory:
- Network analysis tools
- The synchronization problem and Network Time Protocol (NTP)
- MQTT and Kafka
- Multimedia communications and Quality of Service
- Optimization of an actual industrial infrastructure
- Programming of networked embedded systems

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

Lectures and laboratory exercises on computers.

Learning assessment procedures

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

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

Knowledge of theoretical notions and demonstration of knowing how to use the various tools covered in laboratory exercises.

Criteria for the composition of the final grade

Final score: oral exam score + project score.

Exam language

Inglese/English

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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.

Graduation

Deadlines and administrative fulfilments

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

Need to activate a thesis internship

For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.

Final examination regulations

Upon completion of the Master’s degree dissertation, students are awarded 24 CFU, which equates to no more than 4-5 months of full-time work.

Goals
The primary goal of a dissertation is to develop an original study that may include an application project or a theoretical topic related to specific design issues, or a critical review of the most recent developments in a given field of study. During the preparation of the dissertation, under the guidance of the Supervisor and co-supervisors (if any), the student is expected to conduct an in- depth study of the chosen topic, while gaining the ability to summarise and creatively apply the knowledge acquired. The dissertation should focus on topics of engineering and computer science, or closely related areas of study. The work shall consist in the written presentation of activities that may be structured as follows:

  1. design and development of applications or systems;
  2. critical analysis of contributions from the scientific literature;
  3. original research contributions.

The dissertation shall be written in English and can be presented either in English or in Italian, also relying on multimedia tools such as presentations and videos.

Assessment methods and examination procedures
Each dissertation can be either internal or external, depending on whether it is carried out at the University of Verona or in collaboration with another institution. For each dissertation a Supervisor, one or more co-supervisors (optional) and an Examiner will be appointed. The Examiner is appointed by the Computer Science Teaching Committee at least 20 days before the presentation of the dissertation, once the student's eligibility to take the Master's degree examination has been verified. With regard to the legal aspects related to the dissertation and its scientific outcomes (e.g. intellectual property of research outcomes), please refer to the relevant legislation and the University Regulations.
Evaluation of the dissertation
The Supervisor, the co-supervisor/s (if any) and the Examiner will evaluate the dissertation based on the following criteria:

  1. level of in-depth analysis carried out, in relation to the most recent developments in the areas related to information technology, with a focus on medical and biological applications;
  2. scientific and/or technological outcomes of the dissertation;
  3. student’s critical thinking;
  4. student’s experimental and/or formal development;
  5. student’s ability to carry out independent work (this point will not be assessed by the Examiner);
  6. value of the methodologies used;
  7. accuracy in planning and writing the dissertation.

Graduation mark
The graduation mark (based on a 110-point scale) is a whole value between 66/110 and 110/110 and is calculated by adding together the following elements (then rounding the result to the nearest whole number, e.g. 93.50 => 94; 86.49 => 86):

  • 1) the average of the marks gained in the modules, weighted according to CFU, converted to a 110-point scale;
  • 2) evaluation of the dissertation and the oral presentation during the final examination, based on the following methods:
    • a) each of the points 1-7 listed above will be assigned a coefficient between 0 and 1 (fractional coefficient with one decimal place);
    • b) the quality of the presentation will be assessed by awarding a coefficient between 0 and 1 (fractional coefficient with one decimal place);
    • c) the sum of the points resulting from (a) and (b).

The Graduation Committee may award one extra point in the following cases: cum laude honours obtained in the exams taken during the degree programme; participation in internships officially recognised by the Computer Science Teaching Committee; taking extra modules; and the achievement of the degree in a time that is shorter than the normal duration of the degree programme. If the final score is 110/110, the Graduation Committee may award cum laude honours by unanimous decision.

External dissertations
An external dissertation is a work carried out in collaboration with an institution/body other than the University of Verona. In this case, the topic of the dissertation must be agreed in advance with a Supervisor from the University of Verona. In addition, the student must indicate at least one co- supervisor belonging to the external institution/body, who will support the student during the work on the dissertation. The Supervisor and the co- supervisors must be indicated in the online graduation application. The insurance aspects relating to the student's stay at the external institution are regulated by the regulations in force at the University of Verona. If the dissertation involves a period of training at the external institution/body, then it is necessary that the University of Verona enters into a specific agreement with such institution/body. The scientific outcomes of the dissertation will be available to all parties involved. In particular, the contents and results of the dissertation are to be considered public. For all matters not strictly scientific (e.g. agreements, insurance) the resolution of the Academic Senate of 12 January 1999 shall be taken as a reference.

Supervisor, co-supervisors, examiners
The dissertation presentation is introduced by the Supervisor. Professors belonging to the Department of Computer Science may be appointed as Supervisors, as well as any external lecturers who are deemed suitable by the Teaching Committee based on their area of study and level of expertise.
In addition to those who have the above requirements to be appointed as Supervisor, the following individuals may be appointed as co-supervisors: researchers working in external research institutes, research grant holders, post-doctoral fellowship holders, PhD students, technical staff of the Department, external experts appointed by an Italian University, corporate officers who have a remarkable experience in the field relevant to the topic of the dissertation. Examiners may be appointed among lecturers and researchers at the Department of Computer Science of the University of Verona, who are deemed to be experts in the specific field of the dissertation topic.

Graduation Committee
The Graduation Committee shall include five members, of which at least four are professors in the Master's degree programme in Computer Engineering for Robotics and Smart Industry. Based on the number of graduates, the Computer Science Teaching Committee will identify the most appropriate organisational methods for administering the examination, and it shall make available the calendar of tests at least one week before the examination itself. The procedures and deadlines for the submission of the graduation application are established by the Computer Science Teaching Committee and by the relevant offices.

List of thesis 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

Career management


Student login and resources


Erasmus+ and other experiences abroad


Attendance modes and value