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, 2018 Jan 31, 2019
II semestre Mar 4, 2019 Jun 14, 2019
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2019 Feb 28, 2019
Sessione estiva d'esame Jun 17, 2019 Jul 31, 2019
Sessione autunnale d'esame Sep 2, 2019 Sep 30, 2019
Degree sessions
Session From To
Sessione Estiva Jul 18, 2019 Jul 18, 2019
Sessione Autunnale Oct 17, 2019 Oct 17, 2019
Sessione Invernale Mar 18, 2020 Mar 18, 2020
Holidays
Period From To
Sospensione dell'attività didattica Nov 2, 2018 Nov 3, 2018
Vacanze di Natale Dec 24, 2018 Jan 6, 2019
Vacanze di Pasqua Apr 19, 2019 Apr 28, 2019
Festa del Santo Patrono May 21, 2019 May 21, 2019
Vacanze estive Aug 5, 2019 Aug 18, 2019

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

B C D F G L M O P Q R S V

Belussi Alberto

symbol email alberto.belussi@univr.it symbol phone-number +39 045 802 7980

Bombieri Nicola

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

Bonacina Maria Paola

symbol email mariapaola.bonacina@univr.it symbol phone-number +39 045 802 7046

Boscaini Maurizio

symbol email maurizio.boscaini@univr.it

Busato Federico

symbol email federico.busato@univr.it

Calanca Andrea

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

Carra Damiano

symbol email damiano.carra@univr.it symbol phone-number +39 045 802 7059

Castellani Umberto

symbol email umberto.castellani@univr.it symbol phone-number +39 045 802 7988

Cicalese Ferdinando

symbol email ferdinando.cicalese@univr.it symbol phone-number +39 045 802 7969

Cristani Matteo

symbol email matteo.cristani@univr.it symbol phone-number 045 802 7983

Cristani Marco

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

Cubico Serena

symbol email serena.cubico@univr.it symbol phone-number 045 802 8132

Dall'Alba Diego

symbol email diego.dallalba@univr.it symbol phone-number +39 045 802 7074

Dalla Preda Mila

symbol email mila.dallapreda@univr.it

Farinelli Alessandro

symbol email alessandro.farinelli@univr.it symbol phone-number +39 045 802 7842

Favretto Giuseppe

symbol email giuseppe.favretto@univr.it symbol phone-number +39 045 802 8749 - 8748

Fummi Franco

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

Giachetti Andrea

symbol email andrea.giachetti@univr.it symbol phone-number +39 045 8027998

Giacobazzi Roberto

symbol email roberto.giacobazzi@univr.it symbol phone-number +39 045 802 7995

Lovato Pietro

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

Maris Bogdan Mihai

symbol email bogdan.maris@univr.it symbol phone-number +39 045 802 7074

Masini Andrea

symbol email andrea.masini@univr.it symbol phone-number 045 802 7922

Mastroeni Isabella

symbol email isabella.mastroeni@univr.it symbol phone-number +390458027089

Menegaz Gloria

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

Merro Massimo

symbol email massimo.merro@univr.it symbol phone-number 045 802 7992

Muradore Riccardo

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

Oliboni Barbara

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

Paci Federica Maria Francesca

symbol email federicamariafrancesca.paci@univr.it symbol phone-number +39 045 802 7909

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

Rizzi Romeo

symbol email romeo.rizzi@univr.it symbol phone-number +39 045 8027088

Romeo Alessandro

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

Segala Roberto

symbol email roberto.segala@univr.it symbol phone-number 045 802 7997

Setti Francesco

symbol email francesco.setti@univr.it symbol phone-number +39 045 802 7804

Villa Tiziano

symbol email tiziano.villa@univr.it symbol phone-number +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 enrollment year.

CURRICULUM TIPO:

1° Year 

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

2° Year   activated in the A.Y. 2019/2020

ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activities
4
F
-
Final exam
24
E
-
ModulesCreditsTAFSSD
12
B
ING-INF/05
12
B
ING-INF/05
6
B
ING-INF/05
activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
6
B
INF/01
6
B
ING-INF/05
Other activities
4
F
-
Final exam
24
E
-
Modules Credits TAF SSD
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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S02709

Credits

6

Language

Italian

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

II semestre dal Mar 4, 2019 al Jun 14, 2019.

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

Learning outcomes

The aim of the course is to provide the foundations of computational complexity theory. The focus will be on: the theory of NP-completeness; approximation algorithms and basic approaches for the analysis of the approximation guarantee of algorithms for hard problems.

The students who have successfully attended the course will be able to precisely formalize a computational problem, also in a research context, and analyze the computational resources its solution requires.

With the skills and knowledge acquired, students will be able to employ reductions, standard techniques in complexity theory, to analyze the structural properties of computational problems and identify possible alternative approaches (approximation, parameterization) in the absence of (provably) efficient solutions

After attending the course the students will be able to: classify intractable computational problems; understand and verify a formal proof; read and understand a scientific article where a new algorithm is presented together with the analysis of its computational complexity.

Program

Computational models, computational resources, efficient algorithms and tractable problems.

Relationships among computational problems. Polynomial reductions of one problem into another. The classes P, NP, co-NP. Notion of completeness. Proofs od NP-completeness: Cook's theorem; proofs of completeness using appropriate reductions. Search and Decision Problems. Self-Reducibility of NP-complete problems and existence of non-selfreducible problems. Recap of basic notions of computability: Turing Machines and Diagonalization. Hierarchy theorems for time complexity classes. Separability of classes and the existence of intermediate problem under the hypothesis the P is not equal NP.

Space Complexity. Models and fundamental difference between the use of time resource and the space resource. The space complexity classes NL and L and their relationship with the time complexity class P. The centrality of the reachability problem for the study of space complexity. Completeness for space complexity classes: Log-space reductions; NL-completeness of reachability. Non-determinism and space complexity. Savitch theorem and Immelmann-Szelepcsenyi theorem. The classes PSPACE and NPSPACE. Examples of reductions to prove PSPACE-completeness.

Introduction to the approximation algorithms for optimisation problems. Examples of approximation algorithms. Classification of problems with respect to their approximabuility. The classes APX, PTAS, FPTAS. Notion of inapproximability; the gap technique to prove inapproximability results; examples of approximation preserving reductions. Examples of simple randomised algorithms in solving hard problems.


Recommended Prerequisites
-------------------------
To attend the course in a productive way, a student should be confident with the following topics:
1. Basic data structures as list, stack, queue, tree, heap.
2. Graph representation and fundamental graph algorithms:
2.1 Graph visit: BFS, DFS.
2.2 Topological ordering. Connected component.
2.3 Minimal spanning tree. Kruskal and Prim algorithm.
2.4 Single-source shortest path: Dijkstra algorithm and Bellman-Ford one.
2.5 All-pairs shortest path: Floyd-Warshall algorithm and Johnson one.
2.6 Max flow: Ford-Fulkerson algorithm.

A recommended book to revise the above topics is ``Introduction to Algorithms" di T. H. Cormen, C. E. Leiserson, R. L. Rivest e C. Stein (3 ed.).

Reference texts
Author Title Publishing house Year ISBN Notes
J. Kleinberg, É. Tardos Algorithm Design (Edizione 1) Addison Wesley 2006 978-0321295354
Ingo Wegener Complexity Theory Springer 2005
Michael Sipser Introduction to the Theory of Computation PWS 1997 053494728X
Cristopher Moore, Stephan Mertens The Nature of Computation Oxford 2011

Examination Methods

The exam verifies that the students have acquired sufficient understanding of the basic complexity classes and the necessary skills to analyse and classify a computational problem.

The exam consists of a written test with open questions. The test includes some mandatory exercises and a set of exercises among which the student can choose what to work on. The mandatory exercises are meant to evaluate the ability of the student to apply knowledge: reproducing (simple variants of) theoretical results and algorithms seen in class for classical problems. "Free-choice" exercises test the analytical skills acquired by the students to model "new" toy problems and analyse its computational complexity using reductions.

The grade for the module "complexity" is averaged (50%) with the grade for the module algorithm to determine the final grade.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Type D and Type F activities

Documents and news

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: 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.

Graduation

Deadlines and administrative fulfilments

For deadlines, administrative fulfilments and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.

Need to activate a thesis internship

For thesis-related internships, it is not always necessary to activate an internship through the Internship Office. For further information, please consult the dedicated document, which can be found in the 'Documents' section of the Internships and work orientation - Science e Engineering service.

Final examination regulations

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 dell'analisi dei dati Various topics

Attendance

As stated in the Teaching Regulations for the A.Y. 2022/2023, attendance at the course of study is not mandatory.
 


Career management


Student login and resources


Erasmus+ and other experiences abroad