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

4S02789

Credits

6

Coordinator

Not yet assigned

Language

Italian

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

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

The teaching is organized as follows:

Teoria

Credits

4

Period

II semestre

Academic staff

Alessandro Farinelli

Laboratorio

Credits

2

Period

II semestre

Academic staff

Alessandro Farinelli

Learning outcomes

The class presents the main techniques for problem solving, based on the central paradigm of symbolic and probabilistic representations. The objective is to provide the students with the ability to design, apply and evaluate algorithms for difficult problems, meaning that their mechanical solution captures aspects of artificial intelligence or computational rationality.

At the end of the course the student must demonstrate to know and understand the main techniques for state space search, to understand the fundamental concepts related to constrained networks and to know the basic concepts related to probabilistic reasoning and reinforcement learning.

This knowledge will allow the student to: i) apply the state space search techniques to problems of different nature; ii) apply the main solution algorithms for constrained networks both in the context of satisfiability and optimization; iii) use the main solution techniques related to probabilistic reasoning, with particular emphasis on Bayesian networks, Markov decision processes and reinforcement learning.

At the end of the course the student will be able to: i) choose the most appropriate solution technique for different problems; ii) continue independently the studies in Artificial Intelligence, deepening the topics covered in class, both on other texts and on scientific publications.

Program

Problem solving as search in a state space; un-informed search procedures; heuristic search procedures; adversarial search.
Problem solving based on constraint processing (satisfaction and optimization); Solution techniques based on search (Backtracking, Branch and Bound) and inference (Join Tree Clustering, Bucket Elimination);
Intelligent agents: multi-agent systems, coordination.
Probabilistic reasoning: i) Bayesian networks (definitions, main concepts and inference methods); ii) Markov decision processes (definitions and main solution techniques); iii) reinforcement learning (basic concepts and solution
techniques, e.g. Q-Learning).
Implementing (through assisted software development) the main solution techniques presented during the course related to state space search and probabilistic reasoning.

Students can find teaching material and further information on this course at this link: http://profs.sci.univr.it/~farinelli/courses/ia/ia.html

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Teoria Stuart Russell, Peter Norvig Artificial Intelligence: A Modern Approach (Edizione 2) Prentice Hall 2003 0137903952
Teoria Rina Dechter Constraint Processing (Edizione 1) Morgan Kaufmann 2003 ISBN 978-1-55860-890-0
Teoria Richard S. Satto and Andrew G. Barto Reinforcement Learning: an introduction MIT press 1998 ISBN 0-262-19398-1

Examination Methods

The final grade for the IA module is achieved with a written test and a test in the programming laboratory. The written test requires the student to apply the algorithms and the methodologies studied during the course. The test in the programming laboratory aims at evaluating the software produced by the students during the laboratory course.

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