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..

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
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
Festa di San Zeno - S. 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

A B C D F G L M N O P Q R S T Y Z

Antelmi Elena

symbol email elena.antelmi@univr.it

Barbieri Anna

symbol email anna.barbieri@univr.it

Biesuz Mattia

symbol email mattia.biesuz@unitn.it symbol phone-number 0461 283551

Bombieri Nicola

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

Bontempi Pietro

symbol email pietro.bontempi@univr.it symbol phone-number +39 045 802 7614

Bortolan Lorenzo

symbol email lorenzo.bortolan@univr.it symbol phone-number +39 0464 483 510

Boscaini Maurizio

symbol email maurizio.boscaini@univr.it

Boscolo Galazzo Ilaria

symbol email ilaria.boscologalazzo@univr.it symbol phone-number +39 045 8127804

Buffelli Mario Rosario

symbol email mario.buffelli@univr.it symbol phone-number +39 0458027268

Calanca Andrea

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

Cazzoletti Lucia

symbol email lucia.cazzoletti@univr.it symbol phone-number 045 8027656

Chiurco Carlo

symbol email carlo.chiurco@univr.it symbol phone-number +390458028159

Combi Carlo

symbol email carlo.combi@univr.it symbol phone-number +390458027985

Cristani Marco

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

Daffara Claudia

symbol email claudia.daffara@univr.it symbol phone-number +39 045 802 7942

Dalla Preda Mila

symbol email mila.dallapreda@univr.it

Di Marco Roberto

symbol email roberto.dimarco@univr.it symbol phone-number +39 045 802 7847

Fummi Franco

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

Fusco Salvatore

symbol email salvatore.fusco@univr.it symbol phone-number Office: +39 045 802 7954 Lab: +39 045 802 7086

Galie' Mirco

symbol email mirco.galie@univr.it symbol phone-number +39.045.8027681

Giacopuzzi Simone

symbol email simone.giacopuzzi@univr.it symbol phone-number +39 045 812 7510

Ginesi Michele

symbol email michele.ginesi@univr.it

Gregorio Enrico

symbol email Enrico.Gregorio@univr.it symbol phone-number 045 802 7937

Lovato Pietro

symbol email pietro.lovato@univr.it symbol phone-number +39 045 802 7035

Marzola Pasquina

symbol email pasquina.marzola@univr.it symbol phone-number 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Menegaz Gloria

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

Migliorini Sara

symbol email sara.migliorini@univr.it symbol phone-number +39 045 802 7908

Muradore Riccardo

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

Muscolo Giovanni Gerardo

symbol email giovannigerardo.muscolo@univr.it

Oliboni Barbara

symbol email barbara.oliboni@univr.it symbol phone-number +39 045 802 7077

Perlini Cinzia

symbol email cinzia.perlini@univr.it symbol phone-number +39 0458124038

Piccinelli Fabio

symbol email fabio.piccinelli@univr.it symbol phone-number +39 045 802 7097

Pizzini Francesca Benedetta

symbol email francescabenedetta.pizzini@univr.it symbol phone-number 00390458124301

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

Roberti Andrea

symbol email andrea.roberti@univr.it

Romeo Alessandro

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

Ruzzenente Andrea

symbol email andrea.ruzzenente@univr.it symbol phone-number +39 045 812 4464

Sala Pietro

symbol email pietro.sala@univr.it symbol phone-number 0458027850

Samaila Elena Manuela

symbol email elenamanuela.samaila@univr.it symbol phone-number 045 8127690

Sansonetto Nicola

symbol email nicola.sansonetto@univr.it symbol phone-number 045-8027976

Selmi Luca

symbol email luca.selmi@unimore.it

Storti Silvia Francesca

symbol email silviafrancesca.storti@univr.it symbol phone-number +39 045 802 7850

Tomazzoli Claudio

symbol email claudio.tomazzoli@univr.it

Yengui Ihsen

symbol email ihsen.yengui@univr.it

Zivcovich Franco

symbol email franco.zivcovich@univr.it

Zuccher Simone

symbol email simone.zuccher@univr.it

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.

CURRICULUM TIPO:
Modules Credits TAF SSD
Between the years: 2°- 3°
Between the years: 2°- 3°Altre attività formative: lo studente può scegliere tra le 2 seguenti opzioni: a) 2 CFU di seminari al 2 anno e 7 CFU di tirocinio al 3 anno oppure b) 9 CFU di tirocinio al 3 anno.

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

4S009891

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING

Courses Single

Authorized

The teaching is organized as follows:

Modulo A - teoria
The activity is given by Biomedical Data and Signal Processing - Modulo A Teoria of the courseBachelor's degree in Computer Science

Credits

2

Period

Semester 1

Academic staff

Silvia Francesca Storti

Modulo A - laboratorio
The activity is given by Biomedical Data and Signal Processing - Modulo A Laboratorio of the courseBachelor's degree in Computer Science

Credits

1

Period

Semester 1

Academic staff

Silvia Francesca Storti

Modulo B

Credits

3

Period

Semester 2

Academic staff

Daniela Gandolfi

Learning objectives

The teaching goals of the course will address the applicatiopin of physics and mathematical models to biological systems

Prerequisites and basic notions

-

Program

------------------------
Modulo A - Teoria
------------------------
(1) Main biomedical signals and images. Origin, characteristics and acquisition of the main bioelectric signals (electroencephalographic signal - EEG, magnetoencephalographic – MEG, electrocardiographic - ECG, electromyographic - EMG, spontaneous and induced signals, evoked potentials - EP, event-related potentials - ERP). (2) Analysis techniques in the time and frequency domains. Fundamentals of digital signal processing and characterization in the time domain. Digital filtering methods, sampling, A/D conversion. Classic methods for frequency analysis; frequency bands and power spectrum, periodogram; time/frequency resolution; bispectra and coherence; feature extraction methods. Brain source imaging (direct and inverse problems for EEG and MEG signals) and functional and effective connectivity analysis methods. Applications on in-silico and real signals. (3) Statistical analysis of biomedical data. Review of basic concepts of descriptive and inferential statistics.
------------------------
Modulo A - Laboratorio
------------------------
The course includes a series of laboratories in the computer lab with hands-on activities mainly in MATLAB environment aimed at familiarizing students with the main analysis methods of biomedical signals and images (e.g. ECG, EMG, EEG, evoked potentials). The laboratories complement lectures by consolidating learning and developing problem-solving and hands-on practical skills in the context of bioengineering.
------------------------
Modulo B
------------------------
Introduction to the biophysics of neuronal activity. The equivalent circuit model of the cell membrane. Mathematical modeling of the membrane potential through ordinary differential equations of the single compartment model. The Hodgkin and Huxley equations for the numerical simulation of the action potential. Multi-compartmental and synaptic models. Introduction to numerical simulation of neuron and neuronal network activity. Introduction to computer technologies (Py-Neuron, Nest Simulator) that allow the simulation of neuronal circuits and extended brain regions with single cell resolution.

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

------------------------
Modulo A
------------------------
Teaching methods. Regular lectures with power point presentation and blackboard, laboratory exercises and projects. The course approach is "hands on" where students will experiment the design and data analysis with the most suitable methodologies to solve real-life clinical-medical problems. Educational material will be available to students enrolled in the course on the Moodle platform. This material includes lecture presentations in PDF format and material related to laboratory activities. For further details and supplementary materials, please refer to the reference books.
------------------------
Modulo B
------------------------
Teaching is delivered through streaming lessons. The lessons will provide python programming examples. Slides will be available on the MOODLE Portal page (in compliance with copyright).

Learning assessment procedures

------------------------
Modulo A
------------------------
Assessment is conducted via oral examination preceded by a discussion on hands on activity related to neuronal activity modeling.
------------------------
Modulo B
------------------------
Assessment is conducted via oral examination preceded by a discussion on the group project assigned during the lab.

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

To pass the exam, the students must show that: - they have understood the theoretical and practical concepts of the course; - they are able to use the knowledge acquired during the course to solve the assigned problems related to the processing of biomedical signals and data; - they are able to program in MATLAB environment in the context of signal and biomedical data processing; - they are able to use the knowledge acquired during the course to manage the modeling of neuronal activity.

Criteria for the composition of the final grade

The final grade will be the average of the two grades from the two modules.

Exam language

Italiano

Sustainable Development Goals - SDGs

This initiative contributes to the achievement of the Sustainable Development Goals of the UN Agenda 2030. More information on sustainability
Salute e benessere (GOAL 3)

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 A.A. 2021/2022 e A.A. 2022/2023 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 3 cfu complessivi, di tipologia D. Solo nel caso in cui la data di acquisizione della certificazione sia precedente al 27/10/2023 (data della delibera del Collegio didattico di Ingegneria dell'Informazione) potranno essere riconosciuti un massimo di 6 CFU, come precedentemente previsto. Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

Per gli immatricolati A.A. 2023/2024 i crediti per certificazioni linguistiche ulteriori a quelle previste dal piano didattico vengono riconosciuti come crediti sovrannumerari taf D.

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 il VADEMECUM DELLE ATTIVITÀ DI TIROCINIO (indirizzo email della Commissione tirocini: tirocini-ismp@ateneo.univr.it ); qui la relativa pagina informativa (con link a moodle); qui informazioni su come attivarlo. 

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

 

List of courses with unassigned period
years Modules TAF Teacher
Subject requirements: mathematics D Franco Zivcovich

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 soon also via the Univr app.

Attendance

The inter-university nature of the course of study lies in the cooperation of the three universities in the provision of faculty. Therefore, teaching delivery takes place at the administrative and teaching site in Verona and not in the partner universities. This means that it is not possible to attend this bachelor's degree program in the University of Trento or Modena-Reggio Emilia; however, it is possible to use the study spaces of the partner universities, thanks to the agreement between them.

As stated in the Didactic Regulations for A.Y. 2022/2023, course attendance is not mandatory.
Please refer to the constantly updated information of the Crisis Unit for teaching delivery methods.


Career management


Student login and resources


Erasmus+ and other experiences abroad


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
THESIS_1: Sensors and Actuators for Applications in Micro-Robotics and Robotic Surgery Various topics
THESIS_2: Force Feedback and Haptics in the Da Vinci Robot: study, analysis, and future perspectives Various topics
THESIS_3: Cable-Driven Systems in the Da Vinci Robotic Tools: study, analysis and optimization Various topics