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. 2015/2016

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, 2015 Jan 29, 2016
II semestre Mar 1, 2016 Jun 10, 2016
Exam sessions
Session From To
Sessione straordinaria Appelli d'esame Feb 1, 2016 Feb 29, 2016
Sessione estiva Appelli d'esame Jun 13, 2016 Jul 29, 2016
Sessione autunnale Appelli d'esame Sep 1, 2016 Sep 30, 2016
Degree sessions
Session From To
Sess. autun. App. di Laurea Nov 25, 2015 Nov 25, 2015
Sess. invern. App. di Laurea Mar 16, 2016 Mar 16, 2016
Sess. estiva App. di Laurea Jul 12, 2016 Jul 12, 2016
Sess. autun 2016 App. di Laurea Nov 23, 2016 Nov 23, 2016
Sess. invern. 2017 App. di Laurea Mar 20, 2017 Mar 20, 2017
Holidays
Period From To
Festività dell'Immacolata Concezione Dec 8, 2015 Dec 8, 2015
Vacanze di Natale Dec 23, 2015 Jan 6, 2016
Vancanze di Pasqua Mar 24, 2016 Mar 29, 2016
Anniversario della Liberazione Apr 25, 2016 Apr 25, 2016
Festa del S. Patrono S. Zeno May 21, 2016 May 21, 2016
Festa della Repubblica Jun 2, 2016 Jun 2, 2016
Vacanze estive Aug 8, 2016 Aug 15, 2016

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 L M O P Q S U

Belussi Alberto

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

Bombieri Nicola

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

Bonnici Vincenzo

vincenzo.bonnici@univr.it +39 045 802 7045

Boscaini Maurizio

maurizio.boscaini@univr.it

Carra Damiano

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

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Daffara Claudia

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

Di Pierro Alessandra

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

Drago Nicola

nicola.drago@univr.it 045 802 7081

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

Gobbi Bruno

bruno.gobbi@univr.it

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Lora Michele

michele.lora@univr.it

Marzola Pasquina

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

Mastroeni Isabella

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

Menegaz Gloria

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

Oliboni Barbara

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

Posenato Roberto

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

Pravadelli Graziano

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

Quaglia Davide

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

Segala Roberto

roberto.segala@univr.it 045 802 7997

Setti Francesco

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

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

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
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)
ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
One course to be chosen among the following
6
B
(ING-INF/05)
12
B
(ING-INF/05)
ModulesCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
Prova finale
6
E
(-)

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
One course to be chosen among the following
6
B
(ING-INF/05)
12
B
(ING-INF/05)

3° Year

ModulesCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
Prova finale
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

4S02709

Coordinatore

Roberto Segala

Credits

12

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

Italian

Period

II semestre, I semestre

Learning outcomes

Provide the foundamental tools to design algorithmic solutions for concrete programs. The algorithms are evaluated and compared based required amount of resources.

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.

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.

Type D and Type F activities

Modules not yet included

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

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


Area riservata studenti


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.

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.