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 LM18-32 Oct 21, 2015 Oct 21, 2015
Sess. invern. App. di Laurea LM18-32 Mar 17, 2016 Mar 17, 2016
Sess. estiva App. di Laurea LM18-32 Jul 13, 2016 Jul 13, 2016
Sess. autun 2016 App. di Laurea LM18-32 Oct 19, 2016 Oct 19, 2016
Sess. invern. 2017 App. di Laurea-LM18-32 Mar 21, 2017 Mar 21, 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 M O P Q R S V

Belussi Alberto

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

Bombieri Nicola

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

Carra Damiano

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

Castellani Umberto

umberto.castellani@univr.it +39 045 802 7988

Cicalese Ferdinando

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

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Cristani Marco

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

Cubico Serena

serena.cubico@univr.it 045 802 8132

Dalla Preda Mila

mila.dallapreda@univr.it

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Favretto Giuseppe

giuseppe.favretto@univr.it +39 045 802 8749 - 8748

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Franco Giuditta

giuditta.franco@univr.it +39 045 802 7045

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

Mastroeni Isabella

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

Menegaz Gloria

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

Merro Massimo

massimo.merro@univr.it 045 802 7992

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

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Schuster Peter Michael

peter.schuster@univr.it +39 045 802 7029

Segala Roberto

roberto.segala@univr.it 045 802 7997

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Villa Tiziano

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

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.

CURRICULUM TIPO:
ModulesCreditsTAFSSD
12
B
(ING-INF/05)
12
B
(ING-INF/05)
6
B
(ING-INF/05)
6
B
(ING-INF/05)
ModulesCreditsTAFSSD
6
B
(INF/01)
6
B
(ING-INF/05)
Altre attivita' formative (taf f)
4
F
-

1° Year

ModulesCreditsTAFSSD
12
B
(ING-INF/05)
12
B
(ING-INF/05)
6
B
(ING-INF/05)
6
B
(ING-INF/05)

2° Year

ModulesCreditsTAFSSD
6
B
(INF/01)
6
B
(ING-INF/05)
Altre attivita' formative (taf f)
4
F
-
Modules Credits TAF SSD
Between the years: 1°- 2°Due insegnamenti a scelta
6
C
(INF/01)
6
C
(INF/01)
6
C
(SECS-P/10)
6
C
(INF/01)
Between the years: 1°- 2°

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

Teacher

Romeo Rizzi

Credits

6

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Language

Italian

Period

II semestre dal Mar 1, 2016 al Jun 10, 2016.

To show the organization of the course that includes this module, follow this link:  Course organization

Learning outcomes

The goal of this course is to familiarize with the main techniques and methodologies for the design and analysis of efficient algorithms.
We also present some more advanced paradigms and introduce a few approaches
for the dealing with NP-hard problems (approximation algorithms, implicit enumeration and branch & bound algorithms).

Recommended Prerequisite
------------------------
To attend the course lessons in a productive way, a student should be aware of the complexity issues related to problems and algorithms and interested in the design of efficient algorithms.

PROGRAMMING: c/c++ is the reference programming language.

ALGORITHMS: The student should be confident with the following concepts:
1. problems and formulations, encodings and instances
2. running time, memory consumption, worst case/average/amortized analysis, asymptotic growth and notation
3. Basic data structures as list, stack, queue, tree, heap.
4. Sorting
5. Graph representation and fundamental graph algorithms:
5.1 Graph visit: BFS, DFS.
5.2 Topological ordering. Connected component.
5.3 Minimal spanning tree. Kruskal and Prim algorithm.
5.4 Single-source shortest path: Dijkstra algorithm and Bellman-Ford one.
5.5 All-pairs shortest path: Floyd-Warshall algorithm and Johnson one.
5.6 Max flow: Ford-Fulkerson algorithm.

Program

We follow a direct approach driven by the eager of solving
interesting algorithmic problems together.
Just to draw a path, that could be the following.

Main concepts recall about computational problems: definition, instances, encoding, precise and approximate models. Optimization computational problem.
Main concepts recall about algorithms: computational resources, input encoding, input size/cost, computational time. Worst and average analysis. Computational time and growth order.
Computational time vs. hardware improvements: main relations. Efficient algorithms and tractable problems.

Recursion and induction
-----------------------
examples of the inductive approach in solving problems.

Divide et impera paradigm
-------------------------
Definition and application to some problems.

Greedy paradigm
---------------
Definition and application to some problems.

Dynamic programming paradigm
----------------------------
Definition and application to some problems.
Memoization and Dynamic programming.

Branch & Bound technique
------------------------
Definition and application to some problems.
Lower bounds and upper bounds.

Approximations algorithms
-------------------------
A few classical examples (node cover, set cover, Christofides for the metric TSP, an FPTAS for the knapsack).

Fixed parameter tractability
----------------------------
A few examples.
Kernels, iterative compression, color coding.

Examination Methods

The final grade for Algorithms and Complexity is the rounded up average of the mark of Algorithms and the mark of Complexity, where a 30+lode accounts for a 33.
There is no need to give the two exams within a same session: both marks keep validity over the year and, for Algorithms, it is the greatest mark collected that counts.

The test for Algorithms lasts 5 houers and takes places in a computer room: the student designs and codes (in c or c++) the most efficient algorithms he can for three given problems.
Past exams with solutions can be found at the web-page of the course:
http://profs.sci.univr.it/~rrizzi/classes/Algoritmi/index.html

Depending on the edition of the course and the agreement with the students, it is also possible to collect add-up marks on the mark of the exam. These can come with active participation and work of service for the course, and through participating to the projects. We refer to the page of the course for an up to date information on the projects:
http://profs.sci.univr.it/~rrizzi/classes/Algoritmi/index.html

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.

Gestione carriere


Graduation

List of theses and work experience proposals

theses proposals Research area
Analisi ed identificazione automatica del tono/volume della voce AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
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
BS or MS theses in automated reasoning Computing Methodologies - ARTIFICIAL INTELLIGENCE
Sviluppo sistemi di scansione 3D Computing Methodologies - COMPUTER GRAPHICS
Sviluppo sistemi di scansione 3D Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Dati geografici Information Systems - INFORMATION SYSTEMS APPLICATIONS
Analisi ed identificazione automatica del tono/volume della voce Robotics - Robotics
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

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.