Studying at the University of Verona

A.A. 2017/2018

Academic calendar

Il calendario accademico riporta le scadenze, gli adempimenti e i periodi rilevanti per la componente studentesca, personale docente e personale dell'Università. Sono inoltre indicate le festività e le chiusure ufficiali dell'Ateneo.
L’anno accademico inizia il 1° ottobre e termina il 30 settembre dell'anno successivo.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates. For further information, please get in touch with Operational unit: Science and Engineering Teaching and Student Services Unit

Definition of lesson periods
Period From To
I sem. Oct 2, 2017 Jan 31, 2018
II sem. Mar 1, 2018 Jun 15, 2018
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2018 Feb 28, 2018
Sessione estiva d'esame Jun 18, 2018 Jul 31, 2018
Sessione autunnale d'esame Sep 3, 2018 Sep 28, 2018
Degree sessions
Session From To
Sessione Estiva Lauree Magistrali Jul 19, 2018 Jul 19, 2018
Sessione Autunnale Lauree Magistrali Oct 18, 2018 Oct 18, 2018
Sessione Invernale Lauree Magistrali Mar 21, 2019 Mar 21, 2019
Holidays
Period From To
Christmas break Dec 22, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Patron Saint Day May 21, 2018 May 21, 2018
Vacanze estive Aug 6, 2018 Aug 19, 2018

Exam calendar

The exam roll calls are centrally administered by the operational unit  Science and Engineering Teaching and Student Services Unit
Exam Session Calendar and Roll call enrolment sistema ESSE3 .If you forget your password to the online services, please contact the technical office in your Faculty.

Exam calendar

Per dubbi o domande Read the answers to the more serious and frequent questions - F.A.Q. Examination enrolment

Academic staff

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

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980
Foto,  February 9, 2017

Bloisi Domenico Daniele

domenico.bloisi@univr.it

Bombieri Nicola

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

Bonacina Maria Paola

mariapaola.bonacina@univr.it +39 045 802 7046

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

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

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

Maris Bogdan Mihai

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

Masini Andrea

andrea.masini@univr.it 045 802 7922

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

Romeo Alessandro

alessandro.romeo@univr.it +39 045 802 7974-7936; Lab: +39 045 802 7808

Segala Roberto

roberto.segala@univr.it 045 802 7997

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:
TeachingsCreditsTAFSSD
12
B
(ING-INF/05)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
6
B
(ING-INF/05)
TeachingsCreditsTAFSSD
6
B
(INF/01)
6
B
(ING-INF/05)
Other activitites
4
F
-
Final exam
24
E
-

1° Anno

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

2° Anno

TeachingsCreditsTAFSSD
6
B
(INF/01)
6
B
(ING-INF/05)
Other activitites
4
F
-
Final exam
24
E
-
Teachings Credits TAF SSD
Between the years: 1°- 2°2 courses to be chosen among the following
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

4S00084

Coordinatore

Andrea Masini

Credits

6

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language of instruction

Italian

Period

II sem. dal Mar 1, 2018 al Jun 15, 2018.

Learning outcomes

The course aims to provide knowledge of classical logic (propositional and first order), intuitionistic logic and modal logic. Will also be treated: i) deductive and semantic methods; ii) completeness results; iii) limiting results.

At the end of the course the student must demonstrate that he has the necessary knowledge to reason with a formal logical system, both in a classical context and in an intuitionist or modal context. Knowing how to transfer the theoretical notions learned in logical informatic contexts, such as the type theory.

This knowledge will allow the student to: i) carry out formal proofs with a deductive system; ii) handling semantical notions for the refutation of logical formulas; iii) reasoning with axiomatic systems.

At the end of the course the student will be able to: i) compare logical systems, ie classics, intuitionists and modals reasoning both syntactically (deductive systems) and semantically (models); continue the studies autonomously within the logic of computer science.

Program

1)Propositional logic:
-propositions and connectives
-semantics
-natural deduction
-soundness and completeness
2)Predicate logics:
-quantifiers
-structures
-similarity types
-semantics
-identity
-natural deduction
-soundness and completeness
3)basic model theory
-equivalence, isomporphism, categoricity
4) Peano Arithmetic
-first and second incompleteness theorems

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
van Dalen, Dirk Logic and Structure. (Edizione 5) Springer 2013 978-1-4471-4557-8

Examination Methods

Oral examination (about 15/20 minutes of interrogation)
In order to pass the exam, the student must have sufficient knowledge of all the subjects (including the proofs of the theorems).
Better is the knowledge of course topics, better is the result of exam.

Tipologia di Attività formativa D e F

Academic year

Course not yet included

Career prospects


Avvisi degli insegnamenti e del corso di studio

Per la comunità studentesca

Se sei già iscritta/o a un corso di studio, puoi consultare tutti gli avvisi relativi al tuo corso di studi nella tua area riservata MyUnivr.
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Entra in MyUnivr con le tue credenziali GIA.

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

University Language Centre - CLA


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.