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..

For the year 2019/2020 No calendar yet available

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


Baruffi Maria Caterina

Belussi Alberto +39 045 802 7980

Bombieri Nicola +39 045 802 7094

Calanca Andrea +39 045 802 7847

Castellani Umberto +39 045 802 7988

Ceccato Mariano

Chiarini Andrea 045 802 8223

Cozza Vittoria

Cristani Marco +39 045 802 7841

Cubico Serena 045 802 8132

Dall'Alba Diego +39 045 802 7074

Farinelli Alessandro +39 045 802 7842

Favretto Giuseppe +39 045 802 8749 - 8748

Fiorini Paolo 045 802 7963

Fummi Franco 045 802 7994

Giachetti Andrea +39 045 8027998

Giacobazzi Roberto +39 045 802 7995

Maris Bogdan Mihai +39 045 802 7074

Melzi Simone +39 045 802 7068

Muradore Riccardo +39 045 802 7835

Murino Vittorio 045 802 7996

Muscolo Giovanni Gerardo

Pravadelli Graziano +39 045 802 7081

Quaglia Davide +39 045 802 7811

Quintarelli Elisa +39 045 802 7852

Romeo Alessandro +39 045 802 7974-7936; Lab: +39 045 802 7808

Setti Francesco +39 045 802 7804

Spoto Nicola Fausto +39 045 8027940

Villa Tiziano +39 045 802 7034

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.

Training offer to be defined

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





English en

Scientific Disciplinary Sector (SSD)


The teaching is organized as follows:





I semestre

Academic staff

Riccardo Muradore





I semestre

Academic staff

Riccardo Muradore

Learning outcomes

The course aims to provide the following knowledge: theoretical foundation of physical human-robot interaction (e.g. bilateral teleoperation and force control), with particular attention to the design of control architectures capable of guaranteeing stability even in the presence of uncertainties and communication delays.
At the end of the course the student will have to demonstrate that s/he has the following skills to apply the acquired knowledge:
- analyze the technical characteristics and structural properties of a control system for direct or teleoperated interaction with the environment;
- derive the mathematical model of the physical robot-environment interaction (direct or teleoperated);
- design a control architecture to ensure stability, performance and safety;
- implement the control architecture in simulators (e.g. Matlab/Simulink) and in operating systems tailored to robotic application (e.g. ROS).
Student must also have the ability to define the technical specifications for a physical human robot-interaction system a (direct or teleoperated) and the ability to choose the most appropriate way to design the control architecture.
Student will have to be able to deal with other engineers (e.g. electronic, automatic, mechanical) to design advanced control architectures for complex physical human-robot interaction systems.
Student will have to show ability to continue its studies independently in the context of the design of architectures based on non-linear and adaptive techniques.


Topics that will be addressed during the course:
- passivity theory
- advanced algorithms for teleoperation
- communication time delay compensation
Topics that will be addressed during the lab activity:
- Tuning of PID controllers
- Implementation of velocity estimators
- Data-driven system identification
- Implementation of bilateral teleoperation algorithms in ROS/Matlab-Simulink

Examination Methods

The exam will consist of a project addressing some topics discussed during the course. The student should have to implement in ROS (and/or in Matlab/Simulink) a teleoperation algorithm, test it, and prepare a brief technical document explaining his/her work.

To pass the exam, the student should:
- have understood the principles related to the design of a bilateral teleoperation system,
- be able to use the knowledge acquired during the course to solve the assigned problem,
- be able to describe their work by explaining and motivating the design choices.

Type D and Type F activities

Training offer to be defined

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.

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.


List of theses and work experience proposals

theses proposals Research area
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning


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.

Career management

Area riservata studenti