Bus serivce Tor Vergata (private)






Navetta A: from Monday to Friday, connections with the Tor Vergata railway station (via Fermi – Municipality of Frascati) and the Macroarea of Sciences MFN, passing through the various Macroareas/ Faculty;

Navetta B: from Monday to Friday (first run at 7.30 AM and last run at 05:40 PM), connects the Metro Station A Anagnina with Campus X/ CLA, passing through the university and stopping at the Metro C Torre Angela.



Electronic Interfaces (block B-opt) (since 2022-23)

Electronic Interfaces (block B-opt) (since 2022-23)
1 YEAR II semester  6 CFU
Christian Falconi A.Y. 2022-23 (new)
Code: 80300103


The goal is to teach the fundamental principles and tools for designing electronic interfaces.
The contents of the course have general validity, but the focus will be on electronic interfaces for mechatronics.
The course is oriented toward design.

Students will need to know and understand the fundamental principles and tools for the analysis and design of electronic interfaces.

Students will have to demonstrate that they are able to design electronic interfaces.

Students will be able to evaluate the design of electronic interfaces.

The students, in addition to illustrating the fundamental principles and tools for the design of electronic interfaces, must be able to explain each design choice.

Students must be able to read and understand scientific texts and articles (also in English) concerning electronic interfaces.


Thévenin equivalent circuit.
Norton equivalent circuit.
Laplace transform
Fourier transform


Fundamentals on electronic devices.
Equivalent circuits (mechanic systems, thermal systems,…).
Diode circuits.
Transistor circuits.
Operational amplifiers (op amps).
Universal active devices.
Non-idealities of op-amps and other universal active devices.
Op-amp circuits.
Simulations of electronic circuits (SPICE).
Electronic interfaces.
Circuits for mechatronics (design examples).

Call for international mobility for study or research – OVERSEAS deadline 27/01/2023

Call for international mobility for study or research – OVERSEAS deadline 27/01/2023

The University of Rome “Tor Vergata” offers the possibility to its students, regularly enrolled within the standard duration of the course of study increased by a year, to spend part of their course of study at a non-European university with which they have signed a collaboration agreement for a period of study lasting one semester, to follow the courses and take the exams.

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Awarding of n. 2 grants for tutoring and teaching-integrative activities

SELEZIONE PER il conferimento di n. 2 assegni per attività di tutorato e didattico-integrative propedeutiche e di recupero DA DESTINARE A studenti del Corso di Laurea Magistrale in Mechatronics Engineering e del Corso di Dottorato in Ingegneria Elettronica dell’Università degli Studi Roma “Tor Vergata”

Bando_tutorato_Mechatronics 2022

DEADLINE: 03/10/2022

Multimedia Processing and Communication (block C-opt)

Multimedia Processing and Communication (block C-opt)
2 YEAR I semester  6 CFU
Tommaso Rossi

Cesare Roseti

ICT and Internet Engineering
A.Y. 2023-24


The course module provides an overview of the technologies involved in the multimedia application evolution from analogue to digital, from linear television to video on demand. To this aim, the module addresses the main TV standards, the TCP/IP protocols involved in modern streaming services, the network architectures and the different service modes.

PREREQUISITES: A good background in TCP/IP protocols.


PARTE I – Digital TV standards, MPEG-2  and  Transport Stream, IP encapsulation over  DVB.

PARTE II – IP multicast, IGMP, IP multicast routing

PARTE III –  Transport protocols for IP multimedia applications; Video streaming applications and CDN, the multimedia protocol stack, RTP and RTCP, multimedia signalling protocols: RTSP, SDP and SIP, Key Performance Indicators.

PARTE IV -Adaptive Streaming over HTTP, MPEG-DASH, Support to multimedia applications over 5G.


2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2021-22

A.Y. 2022-23

A.Y. 2023-24

Computer Vision A.Y. 24-25

Code: 8039787

LEARNING OUTCOMES: Learning basic concepts in digital image processing and analysis as a novel measurement system in biomedical fields. The main algorithms will be illustrated particularly devoted to the image medical fields.

KNOWLEDGE AND UNDERSTANDING: The student acquires knowledge related to the possibility to use an image analysis platform to monitor the dynamics of a given phenomenon and to extract quantitative information from digital images such as object localization and tracking in digital videos.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student acquires the capability to implement the algorithms in Matlab through dedicated lessons during the course with the aim of being able to autonomously develop new codes for the solution of specific problems in different application fields.

The student must be able to integrate the basic knowledge provided with those deriving from the other courses such as probability, signal theory, and pattern recognition. some fundamentals of measurement systems as well as basic metrological definitions will be provided in support of background knowledge.

The student solves a written test and develops a project in Matlab that illustrates during the oral exam. The project can be done in a group to demonstrate working group capabilities.

Students will be able to read and understand scientific papers and books in English and also to deepen some topics. In some cases, students will develop also experimental tests with time-lapse microscopy acquisition in the department laboratory.



Fundamentals of metrology. Basic definitions: resolution, accuracy, precision, reproducibility, and their impact over an image based measurement system. Image processing introduction. Image representation. Spatial and pixel resolution. Image restoration. Deconvolution. Deblurring. Image quality assessment. Image enhancement. Image filtering for smoothing and sharpening. Image segmentation: pixel based (otsu method), edge based, region based (region growing), model based (active contour, Hough transform), semantic segmentation. Morphological operators. Object recognition and image classification. Case study: defects detection, object tracking in biology, computer assisted diagnosis, facial expression in human computer interface.
Matlab exercises.