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. 2021/2022

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
Primo semestre Oct 4, 2021 Jan 28, 2022
Secondo semestre Mar 7, 2022 Jun 10, 2022
Exam sessions
Session From To
Sessione invernale d'esame Jan 31, 2022 Mar 4, 2022
Sessione estiva d'esame Jun 13, 2022 Jul 29, 2022
Sessione autunnale d'esame Sep 1, 2022 Sep 29, 2022
Degree sessions
Session From To
Sessione Estiva Jul 15, 2022 Jul 15, 2022
Sessione Autunnale Oct 14, 2022 Oct 14, 2022
Sessione Invernale Mar 14, 2023 Mar 14, 2023
Holidays
Period From To
Festa di Tutti i Santi Nov 1, 2021 Nov 1, 2021
Festa dell'Immacolata Concezione Dec 8, 2021 Dec 8, 2021
Festività natalizie Dec 24, 2021 Jan 2, 2022
Festa dell'Epifania Jan 6, 2022 Jan 7, 2022
Festività pasquali Apr 15, 2022 Apr 19, 2022
Festa della Liberazione Apr 25, 2022 Apr 25, 2022
Festività Santo Patrono di Verona May 21, 2022 May 21, 2022
Festa della Repubblica Jun 2, 2022 Jun 2, 2022
Chiusura estiva Aug 15, 2022 Aug 20, 2022

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

A B C D F G L M P S

Accordini Simone

simone.accordini@univr.it +39 045 8027657

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072

Bombieri Cristina

cristina.bombieri@univr.it 045-8027209

Bombieri Nicola

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

Combi Carlo

carlo.combi@univr.it 045 802 7985

Constantin Gabriela

gabriela.constantin@univr.it 045-8027102

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fratea Caterina

caterina.fratea@univr.it 045 802 8858

Fummi Franco

franco.fummi@univr.it 045 802 7994

Giacobazzi Roberto

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

Giugno Rosalba

rosalba.giugno@univr.it 0458027066

Laudanna Carlo

carlo.laudanna@univr.it 045-8027689

Liptak Zsuzsanna

zsuzsanna.liptak@univr.it +39 045 802 7032

Malerba Giovanni

giovanni.malerba@univr.it 045/8027685

Marcon Alessandro

alessandro.marcon@univr.it +39 045 802 7668

Maris Bogdan Mihai

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

Marzola Pasquina

pasquina.marzola@univr.it 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Menegaz Gloria

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

Perduca Massimiliano

massimiliano.perduca@univr.it +39 045 802 7984

Sala Pietro

pietro.sala@univr.it 0458027850

Salvagno Gian Luca

gianluca.salvagno@univr.it 045 8124308-0456449264

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.

ModulesCreditsTAFSSD
Further linguistic skills (C1 English suggested)
3
F
-
Stages
3
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S004556

Coordinatore

Zsuzsanna Liptak

Credits

6

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language

English en

Period

Primo semestre dal Oct 4, 2021 al Jan 28, 2022.

Learning outcomes

In this course we study advanced data structures for the analysis of genomic sequences, and in general, of textual data. Knowledge and understanding The course provides an understanding of the basic challenges and fundamental issues in processing textual data such as genomic sequences; knowledge of some of the most common computational problems on strings and sequences in genomic data analysis and other applications; familiarity with the most important text indices and their use in solving these problems, including complexity analysis (time and space). Applying knowledge and understanding At the end of the course the student will be able to translate typical problems of genomic sequence analysis in operations and algorithms on textual data and evaluate the computational cost incurred. Making judgements At the end of the course the student will be able to judge whether a given algorithm or data structure is appropriate for the problem at hand, including the evaluation of the computational cost incurred. Communication At the end of the course the student will be able to correctly formalize algorithms on sequences with or without the use of advanced text data structures. Lifelong learning skills At the end of the course the student will be able to read and understand independently scientific articles and specialized texts which use advanced string data structures for the analysis of genomic sequences or other textual data.

Program

In recent years, we have seen vast progress of research in computational biology, in which the use of dedicated data structures for genomic sequences, and other types of biological sequence data, has been decisive. At the same time, these methods can be, and are being, applied to all other kinds of textual data.

The explosion of the amounts of data available ("big data") is one of the major challenges for computer science today. Much of this data is in form of text (or can be easily rendered in textual form): genomic sequences and other biological sequences, webpages, emails, scanned books, musical data, and many others. In order to be able to efficiently store, process, and extract information from this data, we need dedicated data structures and algorithms, i.e. data structures specifically developed for strings, also referred to as text indexes.

Program of the course:

1) introduction to strings (sequences), their basic properties and fundamental issues: alphabet size, character comparison, string sorting

2) classical exact pattern matching algorithms (non index-based): Knuth-Morris-Pratt, Boyer-Moore, Rabin-Karp, Aho-Corasick

3) Text indexes I:
- tries
- suffix trees

4) Text indexes II:
- suffix arrays, enhanced suffix arrays
- Burrows-Wheeler Transform (BWT), FM-index

For each of these text indexes, we will study their properties, efficient construction, and applications to specific string problems.

No previous knowledge of biology is necessary for following the course.

Examination Methods

Final exam: written and oral. In the written exam, both theoretical questions will be asked (running times and storage space of algorithms, properties of the data structures studied), and concrete examples will have to be solved (compute the suffix tree, suffix array, BWT etc. of a given string, apply certain algorithms). In the oral exam, the student will have the opportunity to explain in detail his/her solution and show to what extent he/she has understood the topics studied.

The exam will show that the student
- has acquired sufficient understanding of the most important issues with respect to handling large textual data (alphabet type, comparison of strings, string sorting, size of textual data)
- can apply, explain, and analyze the algorithms studied for non-index based pattern matching
- can apply, explain, and analyze the data structures studied, in particular construction algorithms for and storage space required by these data structures (inverted index, trie, suffix tree, suffix array, BWT)
- can apply, explain, and analyze some applications of these data structures to problems on strings, such as pattern matching, matching statistics, palindromes, etc.

The exam is the same for all students (whether or not they followed the lectures).

Type D and Type F activities

Le attività formative di tipologia D o F comprendono gli insegnamenti impartiti presso l'Università di Verona o periodi di stage/tirocinio professionale.
Nella scelta delle attività di tipo D, gli studenti dovranno tener presente che in sede di approvazione si terrà conto della coerenza delle loro scelte con il progetto formativo del loro piano di studio e dell'adeguatezza delle motivazioni eventualmente fornite. Dal 1° dicembre 2021 al 27 febbraio 2022 e dal 2 maggio 2022 al 15 luglio 2022, tramite il presente modulo gli studenti possono richiedere l'inserimento di attività didattiche in TAF D ed F che non possono inserire autonomamente nel proprio piano di studi tramite la procedura on-line.

COMPETENZE LINGUISTICHE - dal 1° ottobre 2021 (Delibera del Consiglio della Scuola di Scienze e Ingegneria del 30 marzo 2021) per gli immatricolati dall'A.A. 2021/2022

  • Lingua inglese: vengono riconosciuti automaticamente 3 CFU per ogni livello di competenza superiore a quello richiesto dal corso di studio (se non già riconosciuto nel ciclo di studi precedente).
  • Altre lingue e italiano per stranieri: vengono riconosciuti automaticamente 3 CFU per ogni livello di competenza a partire da A2 (se non già riconosciuto nel ciclo di studi precedente).
Tali CFU saranno riconosciuti, fino ad un massimo di 6 CFU complessivi, di tipologia F se il piano didattico lo consente, oppure di tipologia D.
Ulteriori crediti a scelta per conoscenze linguistiche potranno essere riconosciuti solo se coerenti con il progetto formativo dello studente e se adeguatamente motivati.

COMPETENZE TRASVERSALI
Scopri i percorsi formativi promossi dal  Teaching and learning centre dell'Ateneo, destinati agli studenti iscritti ai corsi di laurea, volti alla promozione delle competenze trasversali:

1° periodo lezioni (1A) From 9/16/21 To 10/30/21
years Modules TAF Teacher
The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
Primo semestre From 10/4/21 To 1/28/22
years Modules TAF Teacher
1° 2° Data Analysis for Biomedical Sciences D Gloria Menegaz (Coordinatore)
1° 2° Introduction to Robotics to students of scientific courses. D Paolo Fiorini (Coordinatore)
1° 2° Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
Modules borrowed from the Faculty of Scienze matematiche fisiche e naturali
1° periodo lezioni (1B) From 11/5/21 To 12/16/21
years Modules TAF Teacher
The fashion lab (1 ECTS) D Caterina Fratea (Coordinatore)
Secondo semestre From 3/7/22 To 6/10/22
years Modules TAF Teacher
1° 2° Introduction to Robotics to students of scientific courses. D Paolo Fiorini (Coordinatore)
1° 2° Introduction to 3D printing D Franco Fummi (Coordinatore)
1° 2° HW components design on FPGA D Franco Fummi (Coordinatore)
1° 2° Rapid prototyping on Arduino D Franco Fummi (Coordinatore)
1° 2° Protection of intangible assets (SW and invention)between industrial law and copyright D Roberto Giacobazzi (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Python programming language D Not yet assigned

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.

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.

Gestione carriere


Graduation


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.