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.

Study Plan

A.A. 2026/2027 A.A. 2025/2026

This information is intended exclusively for future freshmen who will enroll for the 2025/2026 academic year.
If you are already enrolled in this course of study, consult the information available on the course page:

Master's Degree in in Computer Engineering for Intelligent Systems - Enrollment until 2024/2025

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 enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
6
B
ING-INF/04
6
B
ING-INF/05
12
B
ING-INF/05
12
C
ING-INF/06

2° Year   It will be activated in the A.Y. 2026/2027

ModulesCreditsTAFSSD
Final exam
24
E
-
It will be activated in the A.Y. 2026/2027
ModulesCreditsTAFSSD
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
4 modules among:
- 1st year - Embedded operating systems, Embedded & IoT Systems design, Robotics, Computer vision, Advanced visual computing and 3D modeling - delivered in 2025/2026
- 2nd year - Advanced control systems - delivered in 2026/2027
6
B
ING-INF/04
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/05
6
B
ING-INF/04
6
B
ING-INF/05
Between the years: 1°- 2°
3 modules among:
- 2nd year -  Advanced methods for biomedical signal processing, Neurohealth, Medical robotics, Internet of Medical things - delivered in 2026/2027
- 1st or 2nd year - Mathematical modeling for Industrial and medical digital twins, Cloud computing and distributed systems - delivered in 2025/2026 or in 2026/2027
6
C
ING-INF/06
6
C
ING-INF/04 ,MED/50
6
C
ING-INF/06 ,MED/37
6
C
INF/01
6
C
INF/01 ,MED/50
6
C
MAT/07
Between the years: 1°- 2°
Further activities
6
F
-
Between the years: 1°- 2°
12
D
-

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.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Advanced methods for biomedical signal processing (2026/2027)

Teaching code

4S012366

Credits

6

Coordinator

Not yet assigned

Language

English en

Scientific Disciplinary Sector (SSD)

ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING

Courses Single

Authorized

Seminars 0

The teaching is organized as follows:

Teoria

Credits

5

Period

II semestre

Academic staff

Silvia Francesca Storti

Lessons timetable
Laboratorio

Credits

1

Period

II semestre

Academic staff

Silvia Francesca Storti

Lessons timetable

Learning objectives

The aim of this course is to equip students with a fundamental understanding of advanced methods and models used in biomedical signal processing, developing the ability to analyze and solve problems of significant relevance to the biomedical field. At the end of the course, students will be able to: •demonstrate a comprehensive knowledge of the advanced methods for biomedical signals processing; •use the acquired theoretical and practical knowledge to formulate, analyze and solve problems in bioengineering; •assess the traditional methods in the biomedical sciences in order to identify strengths and weaknesses. Overall, this course will equip students with the foundational knowledge and skills needed to effectively process, analyze, and interpret biomedical signals. It will also provide students with the ability to critically evaluate existing approaches and develop novel solutions to address real-world biomedical challenges.