2nd year

Identification and Neural Networks – 6 CFU (opt C1.b)

Simona Ranieri 2nd year, 6 CFU, a.a. 2026-27, II semester, optC1.b, Subjects
Identification and Neural Networks – 6 CFU (opt C1.b)

block optC1.b – MECHATRONICS SYSTEMS AND ICT – Learning and Communication
2nd Year II semester

Course Information
Course Code 80300088
Credits 6 CFU
Offered by ICT and Internet Engineering
SSD2015
SSD2024
note A.Y. 2025-26 (new name “Identification and Neural Networks”)

A.Y. 2023-24 ex Adaptive Systems (block C-opt)

 

Lecturer
Current Lecturer
Prof. Giovanni Luca Santosuosso
✉ santosuosso@ing.uniroma2.it
☏ 06. 7259.7414
Dept. of Electronic Engineering
Previous Lecturer
Patrizio Tomei (4cfu) Eugenio Martinelli (2cfu) A.Y. 2023-24 ex Adaptive Systems (block C-opt)
Giovanni Luca SANTOSUOSSO A.Y. 2024-25 has not been activated
A.Y. 2025-26 (new name “Identification and Neural Networks”
✉

 

 

 

 

Grading Criteria
Evaluation

Resources
Links

https://t0.gstatic.com/faviconV2?client=SOCIAL&type=FAVICON&fallback_opts=TYPE,SIZE,URL&url=https://didatticaweb.uniroma2.it&size=32  DidatticaWeb
ℹ️ Official Course Information (GOMP)

📑 Course Syllabus (details):

Laboratory Calculus – 4 CFU (block D)

Simona Ranieri 2nd year, 4 CFU, a.a. 2026-27, Block D-Computational Methods, I sem, Subjects
Laboratory Calculus – 4 CFU (block D)

block D – COMPUTATIONAL METHODS
2nd Year I semester
Course Information
Course Code 8068589
Credits 4 CFU
Offered by Pure and Applied Mathematics
SSD2015
SSD2024 INFO-01/A
note

 

Lecturer
Current Lecturer
Prof. Hendrik Speleers
✉
☏ 06. 7259.4634
Previous Lecturer
✉

 

 

 

 

 

 

 

Grading Criteria
Evaluation Oral exam and project evaluation

 

Resources
Links

https://t0.gstatic.com/faviconV2?client=SOCIAL&type=FAVICON&fallback_opts=TYPE,SIZE,URL&url=https://didatticaweb.uniroma2.it&size=32  DidatticaWeb
ℹ️ Official Course Information (GOMP)

📑 Course Syllabus (details):  MAT – Laboratory-Calculus (LC) — Speleers

 

CONTROL OF ELECTRICAL MOTORS AND VEHICLES – 6 CFU (C1-C2-optE.b)

Simona Ranieri 2nd year, 6 CFU, a.a. 2026-27, Block C1-ICT LC, Block C2-ICT IEVE, c1-no-opt, c2-no-opt, II semester, optE.b, Subjects
CEM

CEM

block C1 – MECHATRONICS SYSTEMS AND ICT – Learning and communication
block C2 – MECHATRONICS SYSTEMS AND ICT – Interconnected Electric Vehicle Engineering
block OptE.b – ELECTROMECHANICS
2nd Year II semester
Course Information
Course Code 8039782
Credits 6 CFU
Offered by Mechatronics Engineering
SSD2015 ING-INF/04
SSD2024 IINF-04/A
note A.Y. 2025–26: new course name – Control of Electrical Motors and Vehicles (formerly A.Y. 2025-26 ex Control of Electrical Machines)

 

Lecturer
Current Lecturer
Prof. Cristiano Maria Verrelli
✉ verrelli@ing.uniroma2.it
☏ 06. 7259.7310
Previous Complementary Lecturer
✉

 

 

 

 

 

 

 

Grading Criteria
Evaluation Oral examination

 

Resources
Links

https://t0.gstatic.com/faviconV2?client=SOCIAL&type=FAVICON&fallback_opts=TYPE,SIZE,URL&url=https://didatticaweb.uniroma2.it&size=32  DidatticaWeb
ℹ️ Official Course Information (GOMP)

📑 Course Syllabus (details): MECHA – Control of Electrical Motors and Vehicles (CEM) — C.M. Verrelli

 

Identification and Neural Networks – 6 CFU (since 24-25)

Simona Ranieri 2nd year, 6 CFU, a.a. 2024-25, a.a. 2025-26, II semester, optC1.b, Subjects , , , ,
Identification and Neural Networks – 6 CFU (since 24-25)
2 YEAR II semester  6 CFU
Patrizio Tomei (4cfu)
Eugenio Martinelli (2cfu)		 A.Y. 2023-24 ex Adaptive Systems (block C-opt) 
Giovanni Luca SANTOSUOSSO A.Y. 2024-25 not been activated
A.Y. 2025-26
(new name “Identification and Neural Networks”
Didatticaweb
✅ Syllabus📑

Code: 80300088
SSD: ING-INF/04

 

Quantum Computing (D-opt)

Simona Ranieri 2nd year, 8 CFU, a.a. 2025-26, Block D-Computational Methods, II semester, optD, Subjects , , ,
Mathematical-Methods
2 YEAR (Block D)
 2 semester 8 CFU
(from Electronic Engineering)
Prof. SARGENI FAUSTO, AUF DER MAUR MATTHIAS, DI CARLO ALDO, SALAMON ANDREA  A.Y. 2025-26 activated
start in the a.y. 2026-27
Code: 80300140
SSD: FIS/01
https://www.master-mass.eu/

 

  • PREREQUISITES: Basic concepts of Linear Algebra, Mathematical Analysis and Python Programming
  • OBJECTIVE: The lectures are thought to give a solid knowledge of the theoretical Machine Learning (ML) background. A special focus is given to the ML application for data analysis of physical systems. The students will also learn how to implement a typical ML model using the standard libraries in a Python environment.

 

CONTROL OF ELECTRICAL MOTORS AND VEHICLES – 6 CFU (C1-C2-optE)

Simona Ranieri 2nd year, a.a. 2025-26, Block C1-ICT LC, Block C2-ICT IEVE, BLOCK E–Electromechanics, c1-no-opt, II semester, optE, Subjects , , ,
CEM
2 YEAR II semester 6 CFU
Cristiano M. Verrelli  
 

 

 A.Y. 2025-26 (ex Control of Electrical Machines (B-C-E)

 
didatticaweb
 ✅ Syllabus📑

Code:8039782
SSD: ING-INF/04

 

Radar and Localization – 6 CFU (optC2.a)

Simona Ranieri 2nd year, 6 CFU, a.a. 2025-26, Block C2-ICT IEVE, II semester, optC2.a, Subjects , ,
Radar and Localization – 6 CFU (optC2.a)
2 YEAR II semester 6 CFU
Prof. Mauro Leonardi A.Y. 2025-26
 

 

 (By ICT)
Code: 80300159
SSD: ING-INF/03

LEARNING OUTCOMES: Knowledge of the main applications and operations of radar systems with the necessary basic elements (both theoretical and technical-operational).

KNOWLEDGE AND UNDERSTANDING: Being aware, at the system level, performance in terms of scope, discrimination, ambiguity, Doppler filtering

APPLYING KNOWLEDGE AND UNDERSTANDING: knowing how to deal with new problems with the methods learned

MAKING JUDGEMENTS: the ability to choose among the various methods learned the proper one to face new problems and radar design.

Syllabus – Radar Systems

1. Fundamentals

  • General information on radar.

  • Spectrum usage.

  • Radar measurements:

    • Distance.

    • Radial velocity.

    • Angular location.

2. Radar Equation and Propagation

  • Fundamental radar equation.

  • Receiver and antenna noise.

  • Propagation: attenuation and reflections.

  • Losses.

3. Radar Cross Section and Target Models

  • Radar Cross Section (RCS).

  • Target fluctuation models:

    • Slow fluctuation.

    • Rapid fluctuation.

4. Target Detection

  • Detection of fixed targets.

  • Detection of moving targets.

  • Pulse integration.

5. Decision Theory and Radar Detection

  • Decision criteria.

  • Detection with a single pulse.

  • Detection with N pulses.

6. Radar Types

  • Pulsed radar.

  • Continuous Wave (CW) radar.

  • Frequency Modulated Continuous Wave (FMCW) radar.

  • Automotive radar.

MACHINE LEARNING METHODS FOR PHYSICS – 6 CFU (D-opt)

Simona Ranieri 2nd year, 6 CFU, a.a. 2025-26, Block D-Computational Methods, II semester, optD, Subjects , , ,
MACHINE LEARNING METHODS FOR PHYSICS – 6 CFU (D-opt)
2 YEAR (Block D)
 2 semester 6 CFU
(from Physics LM-17 )
Prof. Michele BUZZICOTTI A.Y. 2025-26 program 📑
Code: 80300140
SSD: FIS/02SSD2024: PHYS-02/A
https://www.master-mass.eu/

 

  • PREREQUISITES: Basic concepts of Linear Algebra, Mathematical Analysis and Python Programming
  • OBJECTIVE: The lectures are thought to give a solid knowledge of the theoretical Machine Learning (ML) background. A special focus is given to the ML application for data analysis of physical systems. The students will also learn how to implement a typical ML model using the standard libraries in a Python environment.

 

COMPUTER VISION – 6 CFU (since 2024-25)

Simona Ranieri 2nd year, 6 CFU, a.a. 2024-25, a.a. 2025-26, ALL blocks, Block A-Mechanics and Digital Transition, Block B-Electronics and Digital Transition, Block C-Mechatronic Systems and ICT, Block C1-ICT LC, Block C2-ICT IEVE, c1-no-opt, II semester, Subjects , , ,
COMPUTER VISION – 6 CFU (since 2024-25)
2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2023-24 (ex MEASUREMENT SYSTEMS FOR MECHATRONICS)

A.Y. 2024-25: Computer Vision
didatticaweb
✅ Syllabus📑

Code: 8039787
SSD: ING/INF/07