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.

A.A. 2020/2021

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, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2021 Feb 26, 2021
Sessione estiva d'esame Jun 14, 2021 Jul 30, 2021
Sessione autunnale d'esame Sep 1, 2021 Sep 30, 2021
Degree sessions
Session From To
Sessione Estiva Jul 19, 2021 Jul 19, 2021
Sessione Autunnale Oct 19, 2021 Oct 19, 2021
Sessione Autunnale Dicembre Dec 7, 2021 Dec 7, 2021
Sessione Invernale Mar 17, 2022 Mar 17, 2022
Holidays
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 2021
Epifania Jan 6, 2021 Jan 6, 2021
Vacanze Pasquali Apr 2, 2021 Apr 5, 2021
Santo Patrono May 21, 2021 May 21, 2021
Festa della Repubblica Jun 2, 2021 Jun 2, 2021

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 O P Q S

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it +39 045 8028827 - 47

Belussi Alberto

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

Bombieri Nicola

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

Boscaini Maurizio

maurizio.boscaini@univr.it

Boscolo Galazzo Ilaria

ilaria.boscologalazzo@univr.it +39 045 8127804

Burato Alberto

alberto.burato@univr.it

Calanca Andrea

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

Carra Damiano

damiano.carra@univr.it +39 045 802 7059

Castellini Alberto

alberto.castellini@univr.it +39 045 802 7908

Centomo Stefano

stefano.centomo@univr.it 045 802(7048)

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Cristani Marco

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

Daffara Claudia

claudia.daffara@univr.it +39 045 802 7942

Dall'Alba Diego

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

Dalla Preda Mila

mila.dallapreda@univr.it

Demrozi Florenc

florenc.demrozi@univr.it +39 045 802 7048

Di Pierro Alessandra

alessandra.dipierro@univr.it +39 045 802 7971

Fummi Franco

franco.fummi@univr.it 045 802 7994

Geretti Luca

luca.geretti@univr.it +39 045 802 7850

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

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

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Maris Bogdan Mihai

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

Marzola Pasquina

pasquina.marzola@univr.it 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Masini Andrea

andrea.masini@univr.it 045 802 7922

Mastroeni Isabella

isabella.mastroeni@univr.it +39 045 802 7089

Migliorini Sara

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

Muradore Riccardo

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

Oliboni Barbara

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

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

Segala Roberto

roberto.segala@univr.it 045 802 7997

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

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

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
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
6
C
(ING-INF/04)
12
B
(ING-INF/05)
ModulesCreditsTAFSSD
12
B
(ING-INF/05)
1 module among the following
6
C
(INF/01)
6
C
(ING-INF/04)
Final exam
6
E
-

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
A
(FIS/01)
English language B1 level
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
6
C
(ING-INF/04)
12
B
(ING-INF/05)

3° Year

ModulesCreditsTAFSSD
12
B
(ING-INF/05)
1 module among the following
6
C
(INF/01)
6
C
(ING-INF/04)
Final exam
6
E
-
Modules Credits TAF SSD
Between the years: 2°- 3°
Between the years: 2°- 3°
Training
6
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S02709

Coordinatore

Roberto Segala

Credits

12

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

Italian

Period

II semestre, I semestre

Learning outcomes

The course objective is to provide the foundamental tools to design algorithmic solutions for concrete programs. The algorithms are evaluated and compared based required amount of resources. At the end of the course the student will have to demonstrate knowledge and understanding of the main algorithms for the problems of sorting, selection, priority queues, visit of graphs, shortest paths, minimum spanning trees, maximum flow; have ability to apply acquired knowledge and understanding skills to compare algorithms on the basis of their complexity; know how to choose the right algorithm for a specific situation; know how to develop the skills necessary to expand the knowledge learned in order to understand algorithmic solutions to new problems.

Program

Complexity: complexity of algorithms, asymptotic notation, resolution of recurrence equations.
Sorting and selection: insertion sort, merge sort, heap sort, quick sort, randomized quick sort. Linear algorithms, counting sort, radix sort, bucket sort. Selection algorithms.
Data structures: heap, binary search trees, RB-trees, B-trees, binomial heaps, hash tables, priority queues, disjoint sets, extension of data structures, graphs.
Design and analisis of alsorithms: divide et impera, greedy, dynamic programming, local serch, backtracking, branch and bound.
Foundamental algorithms: minimum spanning tree (Prim and Kruskal), linear programing (simplex and basic elements of the elipsoid method) shortest path with single source (Dijkstra and Bellman-Ford) and multiple source (Floyd-Warshall and Johnson), maximum flow (Ford-Fulkerson, Karp), maximnal matching on bipartite graph.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
T. Cormen, C. Leiserson, R. Rivest, C. Stein Introduzione agli Algoritmi e Strutture Dati (Edizione 2) McGraw-Hill 2005 88-386-6251-7

Examination Methods

The exam consists of a writtene test of three hours, divided into two parts, and possibly of an oral colloquium.

The forst part of the written test consists of several questions with multiple choices. It produces a valuation from 0 to 30. The exam is not passed if the evaluation is below 18. The exam ends if the evaluation is between 18 and 23. The second part of the written test, available only if the evaluation of the first part is at least 24, consists of one or more exercises of increasing complexity. The evaluation is between 24 and 30.

The optional oral examination is available only if the evaluation of the second part of the written test is at least 27.

The evaluation scale is the following. 18-21 (pure notionistic knowledge), 22-24 (acceptable understanding of the arguments), 25-27 (ability to apply the concepts learned in the course), 28-30 (ability to elaborate autonomous ideas based on the concepts learned in the course).

Type D and Type F activities

Le attività formative in ambito D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite.
 

I semestre From 10/1/20 To 1/29/21
years Modules TAF Teacher
Control theory D Riccardo Muradore (Coordinatore)
Biomedical Data and Signal Processing D Silvia Francesca Storti (Coordinatore)
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
II semestre From 3/1/21 To 6/11/21
years Modules TAF Teacher
Introduction to 3D printing D Franco Fummi (Coordinatore)
Python programming language D Vittoria Cozza (Coordinatore)
HW components design on FPGA D Franco Fummi (Coordinatore)
Rapid prototyping on Arduino D Franco Fummi (Coordinatore)
Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Subject requirements: mathematics D Rossana Capuani
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)

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.

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.

Area riservata studenti


Graduation

List of theses and work experience proposals

theses proposals Research area
Analisi e percezione dei segnali biometrici per l'interazione con robot AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
Integrazione del simulatore del robot Nao con Oculus Rift AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
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)
BS or MS theses in automated reasoning Computing Methodologies - ARTIFICIAL INTELLIGENCE
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning
Dati geografici Information Systems - INFORMATION SYSTEMS APPLICATIONS
Analisi e percezione dei segnali biometrici per l'interazione con robot Robotics - Robotics
Integrazione del simulatore del robot Nao con Oculus Rift Robotics - Robotics
BS or MS theses in automated reasoning Theory of computation - Logic
BS or MS theses in automated reasoning Theory of computation - Semantics and reasoning
Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata Various topics
Proposte di Tesi/Stage/Progetto nell'ambito delle basi di dati/sistemi informativi Various topics

Gestione carriere


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.