Courses
The course is based on experiential learning and hands-on group projects focused on learning by doing. Students access advanced biomedical laboratory instrumentation to understand how signals are acquired before being processed and analyzed. The emphasis is on bio-oriented applications and the design of technologies for biomedical and healthcare contexts.
Instructor: Margherita Matarrese, Pierpaolo Fucile
The course combines theory with experiential learning through hands-on activities and group projects. Students analyze signals from different domains, focusing on information extraction and critical comparison of processing techniques. Applications span human-centered and industrial contexts, supporting the design of signal-based technologies.
Instructor: Margherita Matarrese, Pierpaolo Fucile
This course adopts a hands-on and project-based approach, centered on learning by doing in multidisciplinary teams. Medical and engineering students work together on real biomedical signal processing problems using data acquired through advanced laboratory instrumentation. The course promotes integration between medicine and engineering, linking signal acquisition to processing and clinical interpretation.
Instructors: Margherita Matarrese, Leandro Pecchia
The course is built on experiential and hands-on learning, with group projects based on learning by doing. During the first semester, engineering students collaborate with MedTech students, fostering multidisciplinary integration between engineering and medicine. Students have access to advanced research laboratory instrumentation to understand how biomedical signals are acquired and processed, with a final focus on advanced signal processing technologies for healthcare applications.
Instructors: Margherita Matarrese, Pierpaolo Fucile
MedTech design, regulation, sustainability and innovation
The course aims to provide students with theoretical knowledge and practical skills to understand and address the challenges related to the design, regulation, sustainability, and innovation of medical devices and health technologies (MedTech), within a rapidly evolving European and global context.
Students will acquire an integrated and interdisciplinary perspective on the life cycle of biomedical technologies, from the early stages of ideation and co-design to end-of-life management and reuse, encompassing regulation, assessment, manufacturing, and market adoption. The course is designed to train professionals capable of effectively engaging with diverse stakeholders—including clinicians, engineers, regulatory authorities, industry, and patients—with particular attention to environmental sustainability, responsible innovation, and regulatory compliance.
Instructors: Joseph Lovecchio, Karina Ovejero Paredes
Medical devices: design, regulation, sustainability and innovation
The course aims to provide students with the knowledge and practical awareness needed to understand and manage the challenges associated with medical devices and health technologies in clinical practice, within a rapidly evolving European and global healthcare context. Particular emphasis is placed on the adoption, evaluation, and responsible use of medical technologies.
Students will develop an integrated and interdisciplinary understanding of the life cycle of biomedical technologies, from clinical need identification and co-design to regulatory approval, clinical evaluation, implementation in healthcare settings, and end-of-life management. The course prepares students to effectively interact with regulatory authorities, industry partners, and patients, while addressing key issues related to patient safety, regulatory compliance, environmental sustainability, and responsible medical innovation.
Instructors: Leandro Pecchia, Joseph Lovecchio, Karina Ovejero Paredes
Applications of GenAI and deep learning for health and wellbeing
The course focuses on practical applications of generative AI and deep learning in health and wellbeing, with particular attention to large language models, multimodal AI, and digital health solutions. Through real-world use cases such as clinical decision support, patient monitoring, and AI-assisted healthcare services, students gain hands-on insight into how advanced AI systems are deployed in modern healthcare.
Instructors: Luca Bacco e Mario Merone
Advanced processing and AI for biomedical data, signals and images
The course explores advanced techniques for the analysis of biomedical data, signals, and images, with a strong focus on the use of artificial intelligence and machine learning. Its innovative nature lies in a data-driven approach applied to real clinical problems, enabling students to acquire skills that are directly applicable to research and digital healthcare.
Instructors: Luca Bacco e Mario Merone
Master In Applied Artificial Intelligence Engineering
A practical program, built on real-world experiences of Artificial Intelligence–driven transformation, led by professionals who have already implemented AI in complex organizations, transforming multiple sectors across the globe.
Biomedical Signal Processing is an annual course (10 CFU) within CdL in Biomedical Engineering (L8 – ENG) aiming to introduce principles, methods, and tools of engineering and physics for signal processing in medicine and biology. This course provides future biomedical engineers with a solid foundation in methods for extracting, processing, and presenting biomedical signals to derive meaningful information for prognosis, diagnosis, and health monitoring. It covers the principles underlying biomedical signal generation and interpretation, and the application of techniques to extract relevant information from these signals. Additionally, the course imparts essential principles for designing healthcare technologies focused on signal processing.