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. 2019/2020

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, 2019 Jan 31, 2020
II semestre Mar 2, 2020 Jun 12, 2020
Exam sessions
Session From To
Sessione invernale d'esame Feb 3, 2020 Feb 28, 2020
Sessione estiva d'esame Jun 15, 2020 Jul 31, 2020
Sessione autunnale d'esame Sep 1, 2020 Sep 30, 2020
Degree sessions
Session From To
Sessione Estiva Jul 15, 2020 Jul 15, 2020
Sessione Autunnale Oct 16, 2020 Oct 16, 2020
Sessione Autunnale Dicembre Dec 11, 2020 Dec 11, 2020
Sessione Invernale Mar 17, 2021 Mar 17, 2021
Holidays
Period From To
Festa di Ognissanti Nov 1, 2019 Nov 1, 2019
Festa dell'Immacolata Dec 8, 2019 Dec 8, 2019
Vacanze di Natale Dec 23, 2019 Jan 6, 2020
Vacanze di Pasqua Apr 10, 2020 Apr 14, 2020
Festa della Liberazione Apr 25, 2020 Apr 25, 2020
Festa del Lavoro May 1, 2020 May 1, 2020
Festa del Santo Patrono May 21, 2020 May 21, 2020
Festa della Repubblica Jun 2, 2020 Jun 2, 2020
Vacanze estive Aug 10, 2020 Aug 23, 2020

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 R S T V Z

Ballottari Matteo

matteo.ballottari@univr.it 045 802 7098

Baruffi Maria Caterina

mariacaterina.baruffi@univr.it

Bicego Manuele

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

Boscaini Maurizio

maurizio.boscaini@univr.it

Busato Federico

federico.busato@univr.it

Calanca Andrea

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

Canevari Giacomo

giacomo.canevari@univr.it +39 045 8027979

Capaldi Stefano

stefano.capaldi@univr.it +39 045 802 7907

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Cristani Matteo

matteo.cristani@univr.it 045 802 7983

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Dall'Alba Diego

diego.dallalba@univr.it +39 045 802 7074

Della Libera Chiara

chiara.dellalibera@univr.it +39 0458027219

Delledonne Massimo

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

Dell'Orco Daniele

daniele.dellorco@univr.it +39 045 802 7637

Dominici Paola

paola.dominici@univr.it 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

mariapina.donofrio@univr.it 045 802 7801

Drago Nicola

nicola.drago@univr.it 045 802 7081

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

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

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Maris Bogdan Mihai

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

Menegaz Gloria

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

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Paci Federica Maria Francesca

federicamariafrancesca.paci@univr.it +39 045 802 7909

Piccinelli Fabio

fabio.piccinelli@univr.it +39 045 802 7097

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Romeo Alessandro

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

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Storti Silvia Francesca

silviafrancesca.storti@univr.it +39 045 802 7908

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Villa Tiziano

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

Zivcovich Franco

franco.zivcovich@univr.it

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
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
English B1
6
E
-
ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(BIO/18)
1 module among the following
6
C
(FIS/07)

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
English B1
6
E
-

2° Year

ModulesCreditsTAFSSD
12
B
(INF/01)
6
C
(BIO/18)
1 module among the following
6
C
(FIS/07)

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

Ferdinando Cicalese

The teaching is organized as follows:

Algoritmi per bioinformatica

Credits

6

Period

I semestre

Academic staff

Ferdinando Cicalese

Laboratorio di programmazione ii

Credits

6

Period

See the unit page

Academic staff

See the unit page

Learning outcomes

The course aims at providing the fundamental methodological tools for the design and analysis of al-gorithms with emphasis on their employment in the solution of simple bioinformatics problems. The students will learn to implement basic algorithmic solution and fundamental data structures for solving problems in bioinformatics by employing object oriented programming. The course is structured on two modules: Algoritmi per Bioinformatica and Laboratorio di Programmazione II, which are detaled below.

Module 1: The students will learn foundations of algorithm design and analysis. They will be able to model simple (real world) problems in terms of computational problems; to quantify the computational resources necessary to execute an algorithm, hence to compare different algorithmic solutions in terms of their computational cost. In particular, a student who has profitably attended the course, will be able to evaluate the applicability and effectiveness of basic algorithmic design techniques to simple computational problems.

Module 2: The aim of this module is to provide the basic knowledge to implement fundamental algorithms using object oriented programming. The reference programming language is Java. The teaching methodology includes assisted software development and the implementation of specific projects focussed on applications that are relevant to bioinformatics. At the end of the course the student will be able to use the main data structures available in Java and develop new data structures for the implementation of specific software modules.

Program

------------------------
MM: ALGORITMI PER BIOINFORMATICA
------------------------
Basic definitions: Computational Problems and Algorithms Analysis of algorithms: worst case and average case analysis; Algorithmic complexity: asymptotic notations; basic tools for the analysis of algorithms; solution of recurrences; Algorithms for searching sorting and selection. Data Structure for the implementing a dictionary: queues, heaps, binary search trees, hash tables; Design techniques: divide and conquer; greedy; dynamic programming; Graphs and Graph algorithms: graph traversals, basic connectivity problems, topological sorting
------------------------
MM: LABORATORIO DI PROGRAMMAZIONE II
------------------------
Object oriented programming and the Java language. Implementation of simple programs in Java (primitive types and control structures). Definition of classes and methods. Exception management in Java. Recursion. Interfaces and packages. Implementation of sorting algorithms, search (greedy and exhaustive) and main algorithms on graphs, applied to problems that are relevant to bioinformatics. All the teaching material for this course is available on the course web page hosted on the teachers' web site.

Examination Methods

------------------------
MM: ALGORITMI PER BIOINFORMATICA
------------------------
The exam verifies that the students have acquired sufficient confidence and skill in the use of basic algorithmic design and algorithmic analysis tools. 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 student's knowledge of classical algorithms and analysis tools as seen during the course. "Free-choice" exercises test the ability of students to model "new" toy problems and design and analyse algorithmic solutions for it. The exam can also be passed via two midterm tests (structured as the main final exam). The relative weight of the midterm tests is proportional to the part of the course on which their are based. The overall result of the midterm exams is only valid towards the registration at the one of the exams in February session.
------------------------
MM: LABORATORIO DI PROGRAMMAZIONE II
------------------------
The exam for "Programming Laboratory II" involves the implementation and verification of code written in Java language and it is performed using the computer. The exam can be carried out by partial tests or by a single test. Partial exam is made up of a computer test (conducted in the lab during the course) and a project (developed during the course) that will be presented in an oral exam to the teacher at the end of the course. The final vote is given by the average of the votes of the two partial tests. Exam without partial testing is a single computer test performed at the exam dates. All tests and projects are individual work. Cheating is strictly forbidden and will determine lowering of grades for all students involved.

----------------------
The final overall grade for "Algorithms" is given by the average of the grades achieved for the module "Algorithms for Bioinformatics" and the grade achieved for the module "Programming Laboratory II".

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
J. Kleinberg, É. Tardos Algorithm Design (Edizione 1) Addison Wesley 2006 978-0321295354
Neil C. Jones, Pavel A. Pevzner An introduction to bioinformatics algorithms (Edizione 1) MIT Press 2004 0-262-10106-8
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein Introduction to Algorithms (Edizione 3) MIT Press 2009 978-0-262-53305-8

Type D and Type F activities

1° periodo di lezioni From 9/30/19 To 12/14/19
years Modules TAF Teacher
The fashion lab (1 ECTS) D Maria Caterina Baruffi (Coordinatore)
I semestre From 10/1/19 To 1/31/20
years Modules TAF Teacher
Python programming language D Maurizio Boscaini (Coordinatore)
II semestre From 3/2/20 To 6/12/20
years Modules TAF Teacher
CyberPhysical Laboratory D Andrea Calanca (Coordinatore)
C++ Programming Language D Federico Busato (Coordinatore)
LaTeX Language D Enrico Gregorio (Coordinatore)
Matlab-Simulink programming D Bogdan Mihai Maris (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
Corso Europrogettazione D Not yet assigned
The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka. D Matteo Cristani

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.

Graduation

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

Gestione carriere


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.