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, 2015 Jan 29, 2016
II semestre Mar 1, 2016 Jun 10, 2016
Exam sessions
Session From To
Sessione straordinaria Appelli d'esame Feb 1, 2016 Feb 29, 2016
Sessione estiva Appelli d'esame Jun 13, 2016 Jul 29, 2016
Sessione autunnale Appelli d'esame Sep 1, 2016 Sep 30, 2016
Degree sessions
Session From To
Sess. autun. App. di Laurea Oct 12, 2015 Oct 12, 2015
Sess. autun. App. di Laurea Nov 26, 2015 Nov 26, 2015
Sess. invern. App. di Laurea Mar 15, 2016 Mar 15, 2016
Sess. estiva App. di Laurea Jul 19, 2016 Jul 19, 2016
Sess. autun. 2016 App. di Laurea Oct 11, 2016 Oct 11, 2016
Sess. autun 2016 App. di Laurea Nov 30, 2016 Nov 30, 2016
Sess. invern. 2017 App. di Laurea Mar 16, 2017 Mar 16, 2017
Period From To
Festività dell'Immacolata Concezione Dec 8, 2015 Dec 8, 2015
Vacanze di Natale Dec 23, 2015 Jan 6, 2016
Vacanze Pasquali Mar 24, 2016 Mar 29, 2016
Anniversario della Liberazione Apr 25, 2016 Apr 25, 2016
Festa del S. Patrono S. Zeno May 21, 2016 May 21, 2016
Festa della Repubblica Jun 2, 2016 Jun 2, 2016
Vacanze estive Aug 8, 2016 Aug 15, 2016

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


Albi Giacomo

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Angeleri Lidia

symbol email symbol phone-number 045 802 7911

Baldo Sisto

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Bos Leonard Peter

symbol email symbol phone-number +39 045 802 7987

Boscaini Maurizio

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Busato Federico

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Caliari Marco

symbol email symbol phone-number +39 045 802 7904

Cordoni Francesco Giuseppe

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Daffara Claudia

symbol email symbol phone-number +39 045 802 7942

Daldosso Nicola

symbol email symbol phone-number +39 045 8027076 - 7828 (laboratorio)

De Sinopoli Francesco

symbol email symbol phone-number 045 842 5450

Di Persio Luca

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Gregorio Enrico

symbol email symbol phone-number 045 802 7937

Magazzini Laura

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Malachini Luigi

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Mantese Francesca

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Marigonda Antonio

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Mariotto Gino

symbol email symbol phone-number +39 045 8027031

Mariutti Gianpaolo

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Mazzuoccolo Giuseppe

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Orlandi Giandomenico

symbol email giandomenico.orlandi at symbol phone-number 045 802 7986

Rizzi Romeo

symbol email symbol phone-number +39 045 8027088

Rossi Francesco

Schuster Peter Michael

symbol email symbol phone-number +39 045 802 7029

Solitro Ugo

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Zuccher Simone

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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.

One course to be chosen among the following
One course to be chosen among the following
One/two courses to be chosen among the following
Prova finale

2° Year

One course to be chosen among the following
One course to be chosen among the following

3° Year

One/two courses to be chosen among the following
Prova finale
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
Between the years: 1°- 2°- 3°
Other activitites

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



Romeo Rizzi


Romeo Rizzi





Scientific Disciplinary Sector (SSD)



II sem. dal Mar 1, 2018 al Jun 15, 2018.

Learning outcomes

The student of mathematics (L40, Verona) 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, divede 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 (Hamilton 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 2017-18 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
T. Cormen, C. Leiserson, R. Rivest Introduction to algorithms (Edizione 1) MIT Press 1990 0262031418
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 to the mark acquired at the exam by conducting projects aiming at improving aspects and/or materials of the course in a broad sense.
In preparing yourself for this exam,
take profit of the material (text and correction for each previous exam) available at the website of the course:

We also suggest to consult the three files:
prepararsi_esame.pdf, procedura_esame.pdf and dopo_esame.pdf
contained in folder 000-INFO-ESAME-000 contained, at the same page, among the folders of each previous exams. The approach and spirit with which you should elaborate your answers to the exercises is indeed related to some deep methodological messages at the core of the course, and it might turn difficult to achieve full satisfaction and recognizement at the exam without having adopted these approaches which can go easily overlooked.

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.


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.


For schedules, administrative requirements and notices on graduation sessions, please refer to the Graduation Sessions - Science and Engineering service.


Title Info File
Doc_Univr_pdf 1. Come scrivere una tesi 31 KB, 29/07/21 
Doc_Univr_pdf 2. How to write a thesis 31 KB, 29/07/21 
Doc_Univr_pdf 5. Regolamento tesi (valido da luglio 2022) 171 KB, 17/02/22 

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
Proposte Tesi A. Gnoatto Various topics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics Various topics


As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Career management

Area riservata studenti