Studying at the University of Verona

A.A. 2020/2021

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. .

Definition of lesson periods
Period From To
I semestre Oct 1, 2020 Jan 29, 2021
II semestre Mar 1, 2021 Jun 11, 2021
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2021 Feb 26, 2021
Sessione estiva d'esame Jun 14, 2021 Jul 30, 2021
Sessione autunnale d'esame Sep 1, 2021 Sep 30, 2021
Degree sessions
Session From To
Sessione di laurea estiva Jul 22, 2021 Jul 22, 2021
Sessione di laurea autunnale Oct 14, 2021 Oct 14, 2021
Sessione di laurea autunnale - Dicembre Dec 9, 2021 Dec 9, 2021
Sessione invernale di laurea Mar 16, 2022 Mar 16, 2022
Period From To
Festa dell'Immacolata Dec 8, 2020 Dec 8, 2020
Vacanze Natalizie Dec 24, 2020 Jan 3, 2021
Vacanze di Pasqua Apr 2, 2021 Apr 6, 2021
Festa del Santo Patrono May 21, 2021 May 21, 2021
Festa della Repubblica Jun 2, 2021 Jun 2, 2021
Vacanze Estive Aug 9, 2021 Aug 15, 2021

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 or to the service credential recovery .

Exam calendar

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

Academic staff


Albi Giacomo +39 045 802 7913

Baldo Sisto 045 802 7935

Bos Leonard Peter +39 045 802 7987

Caliari Marco +39 045 802 7904

Canevari Giacomo +39 045 8027979

Chignola Roberto 045 802 7953

Cubico Serena 045 802 8132

Daffara Claudia +39 045 802 7942

Dai Pra Paolo +39 0458027093

Daldosso Nicola +39 045 8027076 - 7828 (laboratorio)

Delledonne Massimo 045 802 7962; Lab: 045 802 7058

De Sinopoli Francesco 045 842 5450

Di Persio Luca +39 045 802 7968

Favretto Giuseppe +39 045 802 8749 - 8748

Fioroni Tamara 0458028489

Gnoatto Alessandro 045 802 8537

Gregorio Enrico 045 802 7937

Mantese Francesca +39 045 802 7978

Marigonda Antonio +39 045 802 7809

Mattiolo Davide

Mazzuoccolo Giuseppe +39 0458027838

Monti Francesca 045 802 7910

Nardon Chiara

Orlandi Giandomenico

giandomenico.orlandi at 045 802 7986

Patacca Marco

Rizzi Romeo +39 045 8027088

Sala Pietro 0458027850

Sansonetto Nicola 049-8027932

Schuster Peter Michael +39 045 802 7029

Segala Roberto 045 802 7997

Solitro Ugo +39 045 802 7977

Vincenzi Elia

Zuccher Simone

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.

English language B1 level
Final exam

2° Anno

English language B1 level

3° Anno

Final exam
Teachings Credits TAF SSD
Between the years: 1°- 2°- 3°
Between the years: 1°- 2°- 3°
Other activities

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



Romeo Rizzi


Romeo Rizzi



Scientific Disciplinary Sector (SSD)


Language of instruction



II semestre dal Mar 1, 2021 al Jun 11, 2021.

Learning outcomes

The student will encounter in concrete the concepts of: problems, models, formulations of operations research, but also of instances, algorithms, reductions and mappings among problems of the computer science field. The course will propose some models of operations research, at least the following: linear programming (LP), integer linear programming (ILP), max-flows and min-cuts, bipartite matchings and node covers, minimum spanning trees, shortest paths, Eulerian paths, and some models resorting on dynamic programming among which some knapsack variants. For all these models/problems, except PLI, the student will learn the solving algorithms, the properties on which they hinge, and how to conduct their execution.
However, besides and beyond this, the course aims at building a good and active relationship, practice, and acquaintance, with general mathematical methodologies and techniques (more typical of discrete math and for this reason not yet fully assimilated from our students) and some basic underpinnings of computer science.
In particular, we insist on the dialog with problems and with the art/technique of conjecturing, no occasion is lost to spotlight where invariants and monovariants play a role in proofs, algorithms and data structures. We build up confidence with mathematical induction as an active tool for problem solving, and introducing the dialects of induction most voted to efficiency (divide et impera, recursion with memoization, dynamic programming).
Some basic principles of informatics are underlined, like coding, algorithms, data structures, recursion as a counterpart of mathematical induction and of computability. (In some editions of the course first scratch introductions to numerability and computability have been offered). Coming to efficiency, our central perspective, the use of asymptotic notation is justified and adopted, the classes P, NP, coNP are introduced, and the concepts of good characterizations, good conjectures and good theorems are illustrated in length and complexity theory is advertised as a lively source of new methodologies in the art of facing problems and enquiry their intrinsic structural properties. Several aspects of the role and importance of the art of reducing one problem to another are discussed and clarified. The life cycle of a good conjecture, the workflow linking good conjectures and algorithms, the production and interpretation of counterexamples as a means of dialog with the problem, and the possible use of them in obtaining NP-completeness proofs, are all discussed, investigated and exemplified in action. Explicit emphasis is constantly given to the role and use of certificates.
Meanwhile these transversal and high competences of methodological interest and imprinting are delivered, the students is asked to learn and develop several concrete procedural competences, in particular within LP, and in an algorithmic treatment of graph theory, introduced as a versatile model and an intuitive and expressive language for the formulation of problems.
For a complete and detailed list of all these procedural competences delivered and requested, see the past exams and corrections over the various editions of the course.
The notions from computational complexity introduced in the course, and the attention to the languages of the certificates, will lead the student to recognize with more awareness the structure of a sound proof.
Dealing with instances, problems, models, both from the perspective of algorithms and of models and formulations, will enforce the attitude and competence in casting simple problems from the applications into mathematical models. The knowledge of the paradigmatic results of linear programming theory (duality, complementary slackness, economic interpretation, sensitivity analysis) will provide the student with important tools in obtaining non-trivial insights on the practical problem from the model.


Operations Research offers quantitative methods and models for the optimal management of resources, and optimization of profits, services, strategies, procedures.
This course of Operations Research gets to Mathematical Programming moving from Algorithmics and Computational Complexity.
After revisiting mathematical induction, recursion, divide et impera, with a curiosity driven problem solving approach, we insist on dynamic programming thinking which gets then exemplified in a few classical models of Operations Research and Computational Biology.
With emphasis on method and techniques, we get involved in formulating, encoding and modeling problems, conjecturing about them, reducing one to the other,
and well characterizing them.
The course offers an in-depth introduction to linear programming.
Following the historical path, we introduce graphs as for modeling,
and explore the basic fundamental results in combinatorial optimization and graph theory.


1. Basic Notions

2. Introduction to Algorithms and Complexity
analysis of a few algorithms
design techniques (recursion, divide et impera, recursion with memoization, dynamic programming, greedy)
complexity theory (P, NP, co-NP, good characterizations, good conjectures, examples of NP-completeness proofs)

3. Combinatorial Optimization Models
knapsack problems
Problems on sequences
Problems on DAGs

4. Introduction to Graph Theory
graphs and digraphs as models
a few good characterizations (bipartite, Eulerian, acyclic, planar graphs)
a few NP-hard models (Hamiltonian cycles, cliques, colorability)
shortest paths
minimum spanning trees
maximum flows
bipartite matchings

5. Linear Programming (LP)
the LP and the ILP models (definition, motivations, complexity, role)
geometric method and view (feasibility space,
pivot, duality, dual variables, degeneracy, complementary slackness)
standard and canonical form
simplex method
duality theory
complementary slackness
economic interpretation of the dual variables
sensitivity analysis


At the following page you find a list of available materials (books, notes, videos) about topics covered within the course:

If you find out further effective material help us enlarging this list.


For the 2020-21 edition we are planning to introduce a tutor that will assist and guide the students in performing the exercises suggested during the class and in conducting practical experiences.


Reference texts
Author Title Publishing house Year ISBN Notes
Garey, M. R. and Johnson, D. S. Computers intractability: a guide to the theory of NP-completeness Freeman 1979 0-7167-1045-5
T. Cormen, C. Leiserson, R. Rivest, C. Stein Introduzione agli Algoritmi e Strutture Dati (Edizione 2) McGraw-Hill 2005 88-386-6251-7
Robert J. Vanderbei Linear Programming: Foundations and Extensions (Edizione 4) Springer 2001 978-1-4614-7630-6

Examination Methods

At the end of the course, a written exam with various types of exercises and questions, and several opportunities to gather points to test and prove your preparation. You can add (in full or in part) to the mark acquired at the exam by conducting projects aiming at improving aspects and/or materials of the course in a broad sense.

Up to and included the 2018/19 edition, the exam was taking place in a room by our department in Ca' Vignal.
In the 2019/20 edition (onset of COVID-19) the exams took place from remote, followed by an oral discussion meant only as a check and also as an opportunity for direct confrontation and exchange.
Since many details concerning the exams are subject to dynamic evolution and also determined in the exchanges of ideas and proposals inside the class, and we want to make sure no student gets lost, we redirect the student directly to the reference service site that we can maintain constantly updated:

We warmly advise every student to subscribe to the Telegram group for the current edition of the course and for the testing of the installations, configurations, and environments set up for the exam. All these resources can be conveniently accessed from the URL here above.

We underline a peculiarity of the Operations Research course, the only one in discrete mathematics at the bachelor: the approach and spirit with which you should approach the course and the exam, and what to deliver and elaborate in your answers to the exercises, is actually related to some deep methodological messages that we decided to place at the core of the course. The more the student adopts and interprets these approaches, the more he/she will be proactive in the course and in collaborating to any verification, the more enriching the course and the more fun the exam will be. This will be important in getting the most from the course and achieve full satisfaction and recognition at the exam.

There are 4 exam sessions each academic year (June, July, September, February). The exam is the very same regardless on whether you have attended or not the course. The archives of the past exams, the relative corrections, and the videos of the classes, all can help overcoming the difficulties of the non-attending student.

Tipologia di Attività formativa D e F

Le attività formative in ambito 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.


Primo semestre From 10/4/21 To 1/28/22
years Teachings TAF Teacher
1° 2° 3° Basis of general chemistry D Chiara Nardon

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.
In questo portale potrai visualizzare informazioni, risorse e servizi utili che riguardano la tua carriera universitaria (libretto online, gestione della carriera Esse3, corsi e-learning, email istituzionale, modulistica di segreteria, procedure amministrative, ecc.).
Entra in MyUnivr con le tue credenziali GIA.



List of theses and work experience proposals

theses proposals Research area
Formule di rappresentazione per gradienti generalizzati Mathematics - Analysis
Formule di rappresentazione per gradienti generalizzati Mathematics - Mathematics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics Various topics

Tutorato per gli studenti

I docenti dei singoli Corsi di Studio erogano un servizio di tutorato volto a orientare e assistere gli studenti del triennio, in particolare le matricole, per renderli partecipi dell’intero processo formativo, con l’obiettivo di prevenire la dispersione e il ritardo negli studi, oltre che promuovere una proficua partecipazione attiva alla vita universitaria in tutte le sue forme.

Tutorato finalizzato a offrire loro un’attività di orientamento che possa essere di supporto per gli aspetti organizzativi e amministrativi della vita universitaria.
Le tutor attualemente di riferimento sono:
  • Dott.ssa Luana Uda,
  • Dott.ssa Roberta RIgaglia,

Tirocini e stage

Le attività di stage sono finalizzate a far acquisire allo studente una conoscenza diretta in settori di particolare attività per l’inserimento nel mondo del lavoro e per l’acquisizione di abilità specifiche di interesse professionale.
Le attività di stage sono svolte sotto la diretta responsabilità di un singolo docente presso studi professionali, enti della pubblica amministrazione, aziende accreditate dall’Ateneo veronese.
I crediti maturati in seguito ad attività di stage saranno attribuiti secondo quanto disposto nel dettaglio dal “Regolamento d’Ateneo per il riconoscimento dei crediti maturati negli stage universitari” vigente.

Tutte le informazioni in merito agli stage sono reperibili al link

Modalità di frequenza

Come riportato al punto 25 del Regolamento Didattico per l'A.A. 2021/2022, la frequenza è in generale non obbligatoria, con la sola eccezione di alcune attività laboratoriali. Per queste sarà chiaramente indicato nella scheda del corrispondente insegnamento l'ammontare di ore per cui è richiesta la frequenza obbligatoria.

University Language Centre - CLA


Gestione carriere

In questa pagina lo studente può trovare tutto il necessario per gestire la propria carriera universitaria al meglio, con il supporto della Segreteria Studenti - Carriere di afferenza.