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. 2010/2011

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 4, 2010 Jan 31, 2011
II semestre Mar 1, 2011 Jun 15, 2011
Exam sessions
Session From To
Sessione straordinaria Feb 1, 2011 Feb 28, 2011
Sessione estiva Jun 16, 2011 Jul 29, 2011
Sessione autunnale Sep 1, 2011 Sep 30, 2011
Degree sessions
Session From To
Sessione autunnale Oct 21, 2010 Oct 21, 2010
Sessione straordinaria Dec 15, 2010 Dec 15, 2010
Sessione invernale Mar 24, 2011 Mar 24, 2011
Sessione estiva Jul 19, 2011 Jul 19, 2011
Holidays
Period From To
All Saints Nov 1, 2010 Nov 1, 2010
National holiday Dec 8, 2010 Dec 8, 2010
Christmas holidays Dec 22, 2010 Jan 6, 2011
Easter holidays Apr 22, 2011 Apr 26, 2011
National holiday Apr 25, 2011 Apr 25, 2011
Labour Day May 1, 2011 May 1, 2011
Local holiday May 21, 2011 May 21, 2011
National holiday Jun 2, 2011 Jun 2, 2011
Summer holidays Aug 8, 2011 Aug 15, 2011

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 S V Z

Bombieri Nicola

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

Bonacina Maria Paola

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

Carra Damiano

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

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

Drioli Carlo

carlo.drioli@univr.it +39 045 802 7968

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

Fontana Federico

federico.fontana@univr.it +39 045 802 7032

Fracastoro Gerolamo

gerolamo.fracastoro@univr.it + 39 0458122786

Fummi Franco

franco.fummi@univr.it 045 802 7994

Fusiello Andrea

nome.cognome[at]uniud.it

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Macedonio Damiano

damiano.macedonio@univr.it 045-802.7079

Manca Vincenzo

vincenzo.manca@univr.it 045 802 7981

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

Monti Francesca

francesca.monti@univr.it 045 802 7910

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

Segala Roberto

roberto.segala@univr.it 045 802 7997

Vigano' Luca

luca.vigano@univr.it

Villa Tiziano

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

Zorzi Margherita

margherita.zorzi@univr.it +39 045 802 7908

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)
Altre attivita' formative
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)
Altre attivita' formative
4
F
-
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S02709

Credits

12

Coordinatore

Margherita Zorzi

The teaching is organized as follows:

Complessità

Credits

6

Period

I semestre

Academic staff

Margherita Zorzi

Algoritmi

Credits

6

Period

II semestre

Academic staff

Margherita Zorzi

Learning outcomes

Module: ALGORITMI
-------
The goal of this course is to introduce some advanced paradigms for algorithms development and analysis in order to determine good approximate solutions for hard optimization problems.


Module: COMPLESSITÀ
-------
In this courses, the relevant notions in complexity theory are introduced. Main themes are the relationship between complexity classes and Np-completeness theory. The scope of the courses is to give formal instruments useful in the analysis of the difficulty of computational problems.

Program

Module: ALGORITMI
-------
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.

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

Greedy paradigm
---------------
Definition and application to some problems. Matroids and greedy algorithms.
Huffman Codes

Backtracking technique
----------------------
Definition and application to some problems (main examples: Graham Scan and Knuth-Morris-Pratt algorithm).

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

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


Probabilistic algorithms
------------------------
Definition and few application examples.
Numerical probabilistic algorithms, Monte Carlo algorithms and Las Vegas algorithms. Examples: Buffon's needle, Pattern Matching and Universal hashing.


Local search tecnique
---------------------
Definition and application to some problems.

Approximations algorithms
-------------------------
Definition and some examples.
Simulated annealing.
Tabù search.


Module: COMPLESSITÀ
-------
This is a condensed version of the program. The detailed program (with useful notes for the students) is available in the pdf file "Diario delle Lezioni"

1)Introduction
Computational models, computational resources, tractable problems and feasible algorithms.



2) Computational models and time complexity classes
Deterministic Turing Machine with 1 and k strings
Class TIME(f(n)).
Relationship between k-MdT e 1-MdT (theorem).
Random Access Machine. 

Simulation theorems TM-RAM. 

Thesis of sequential calculus.
Linear speed-up theorem and consequences.
The class P.

Examples of problems in P.


Non deterministic Turing machine(NTM).

Class NTIME(f(n)).

Relationship between NTM and TM.

The class NP.

Examples of problems in NP.
Characterization of problem in NP with polynomial verifier.
The class EXP.



4)Space complexity
.
Input-output TM.
Classes SPACE(f(n)) and NSPACE(f(n)).

Compression Theorem
Classes L e NL.

Examples of problems in L and NL.

Relationship between space and time onf I/O TM

5)Relationship between complexity classes
Proper function.
The reachability method.
Theorems: inclusions between time and space classes. Universal TM.
Lemmata for Time Hierarchy Theorem.

Time Hierarchy Theorem. Corollary P ⊂ EXP.

Space Hierarchy Theorem. Corollary L ⊂ PSPACE.
Gap's Theorem.

Savitch's Theorem with Corollary. Corollary PSPACE=NPSPACE.



6)Reduction and completeness
Reduction and logarithmic reduction.

Examples of reduction: HAMILTON PATH ≤log SAT, PATH ≤log CIRCUIT VALUE, CIRCUIT SAT ≤log SAT.

Examples of reduction by generalization.
Property of reduction: reflexivity and transitivity.
 C-Completeness for a language.

Closure of a class C with respect to reduction.
L, NL, P, NP, PSPACE and EXP are closed w.r.t ≤log.

Table method. Computational table
CIRCUIT VALUE is P-complete.

Cook's theorem.

Examples of NP-complete problems.

7)Some notions on the complement of non deterministic classes
coC
NP and coNP

Examination Methods

Module: ALGORITMI
-------
Written test/ open questions


Module: COMPLESSITÀ
-------
Written test with open questions.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
Christos H. Papadimitriou Computational complexity Addison Wesley 1994 0201530821

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.