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
I semestre Oct 1, 2019 Jan 31, 2020
II semestre Mar 2, 2020 Jun 12, 2020
Exam sessions
Session From To
Sessione invernale d'esame Feb 3, 2020 Feb 28, 2020
Sessione estiva d'esame Jun 15, 2020 Jul 31, 2020
Sessione autunnale d'esame Sep 1, 2020 Sep 30, 2020
Degree sessions
Session From To
Sessione Estiva Jul 15, 2020 Jul 15, 2020
Sessione Autunnale Oct 16, 2020 Oct 16, 2020
Sessione Autunnale Dicembre Dec 11, 2020 Dec 11, 2020
Sessione Invernale Mar 17, 2021 Mar 17, 2021
Holidays
Period From To
Festa di Ognissanti Nov 1, 2019 Nov 1, 2019
Festa dell'Immacolata Dec 8, 2019 Dec 8, 2019
Vacanze di Natale Dec 23, 2019 Jan 6, 2020
Vacanze di Pasqua Apr 10, 2020 Apr 14, 2020
Festa della Liberazione Apr 25, 2020 Apr 25, 2020
Festa del Lavoro May 1, 2020 May 1, 2020
Festa del Santo Patrono May 21, 2020 May 21, 2020
Festa della Repubblica Jun 2, 2020 Jun 2, 2020
Vacanze estive Aug 10, 2020 Aug 23, 2020

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

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

Angeleri Lidia

lidia.angeleri@univr.it 045 802 7911

Ballottari Matteo

matteo.ballottari@univr.it 045 802 7098

Betterle Nico

nico.betterle@univr.it +39 045 8027807

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Boscaini Maurizio

maurizio.boscaini@univr.it

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Capaldi Stefano

stefano.capaldi@univr.it +39 045 802 7907

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Della Libera Chiara

chiara.dellalibera@univr.it +39 0458027219

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Dell'Orco Daniele

daniele.dellorco@univr.it +39 045 802 7637

Dominici Paola

paola.dominici@univr.it 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

mariapina.donofrio@univr.it 045 802 7801

Drago Nicola

nicola.drago@univr.it 045 802 7081

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fratea Caterina

caterina.fratea@univr.it 045 802 8858

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

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Maris Bogdan Mihai

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

Mazzi Giulio

giulio.mazzi@univr.it

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Monti Francesca

francesca.monti@univr.it 045 802 7910

Nardon Chiara

chiara.nardon@univr.it

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

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

Sala Pietro

pietro.sala@univr.it 0458027850

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

silviafrancesca.storti@univr.it +39 045 802 7908

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Valenti Maria Teresa

mariateresa.valenti@univr.it +39 045 812 8450

Villa Tiziano

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

Zivcovich Franco

franco.zivcovich@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 enrolment year.

ModulesCreditsTAFSSD
12
C
CHIM/03 ,CHIM/06
6
A
FIS/01
English B1
6
E
-

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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S008228

Credits

12

The teaching is organized as follows:

Riconoscimento e recupero dell'informazione per bioinformatica

Credits

6

Period

See the unit page

Academic staff

See the unit page

Segnali e immagini i

Credits

6

Period

See the unit page

Academic staff

See the unit page

Learning outcomes

The course is aimed at providing the basic theoretical and applicative tools and techniques for the analysis and management of biological data; in particular the course is focused on topics linked to Pattern Recognition and Image analysis The course comprises two modules as detailed below. Module1: This module is aimed at providing the theoretical and applicative bases of Pattern Recognition, a class of automatic methodo-logies used to recognize and recover information from biological data. In particular, during the course the main techniques of this area will be presented and discussed, in particular linked to representa-tion, classification, clustering and validation. The focus is more on the description of the employed methodologies rather than on the details of applicative programs (already seen in other courses). Af-ter attending the course, the students will be able to analyse a biological problem from a Pattern Re-cognition perspective; they will also have the skills needed to invent, develop and implement the dif-ferent components of a Pattern Recognition System. Module2:

Program

Please refer to the program of the two parts.

Examination Methods

To pass the exam, the student must prove:
- the capability to clearly and concisely describe the different components of a Pattern Recognition System
- the capability to analise, understand and describe a Pattern Recognition system (or a given part of it) relative to a biological problem
- the ability to analyze the typical signal and image processing problems encountered in bioinformatics as well as to devise and implement suitable solutions grounding on the knowledge gained in the theory sessions and using the main available toolboxes;
- the ability to describe the concepts in a clear and exhaustive way;
- the ability to apply the acquired knowledge to solve application scenarios described by means of questions and exercises.

The exam of INFORMATION RETRIEVAL AND SIGNAL AND IMAGE PROCESSING FOR BIOINFORMATICS consists of two parts:
i) a written exam of INFORMATION RETRIEVAL containing questions on topics presented during the course (15 points available). The (i) written part is passed if the grade is greater or equal to 9;
ii) a written exam of SIGNAL AND IMAGE PROCESSING consisting in questions concerning the topics of both the theory and the laboratory sessions, with respective weight of 2/3 and 1/3, and one exercise (15 punti). In case the exam would be in teleconference mode the exam would be be in oral form.

The two parts of the exam can be passed separately: the final grade is the sum of the two grades.
The total exam is passed if each of the two grades is greater or equal to 9. Each evaluation is maintained valid for the whole academic year.

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
C++ Programming Language D Federico Busato (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Corso Europrogettazione D Not yet assigned
The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Matteo Cristani

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.

Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.


Graduation

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

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