- Docente responsabile
- MARCO DOMENICO SANTAMBROGIO
- CCS proponenti
- Ingegneria Informatica
- CFU
- 2
- Ore in presenza
- 12
- N° max studenti
- 100
- Criteri di selezione
- Order of arrival, max 100 people, of which 30 in person
- Parole chiave:
- Deep Learning, Graph Machine Learning, Graphs
- Tag
- Engineering, Artificial intelligence, Health and lifescience, Information technologies
Descrizione dell'iniziativa
Thanks to its ability to model complex relationships between entities, Graph Machine Learning (GML) is now widely applied in fields such as medicine, bioinformatics, computational chemistry, as well as content recommendation systems and cybersecurity. This course aims to introduce the fundamental concepts of machine learning on graphs, with a particular focus on Graph Neural Networks and their applications in biomedical and social network contexts. Students will acquire the skills needed to represent, analyze, and model non-Euclidean structured data, such as protein interaction networks, gene networks, or user interaction graphs. The course includes theoretical lessons covering topics such as graph representation, convolutions, pooling techniques, network architectures, and training strategies. The hands-on sessions, conducted in Python, will allow students to apply the studied models to real-world datasets, including biological networks and social network data. At the end of the course, students will participate in a challenge, where they will be asked to develop and evaluate a GML model to solve a real-world problem, selected from the provided datasets. Completion of the course will be assessed based on participation the final project delivery. By the end of the course, participants will be able to understand the key principles of Graph Machine Learning, read and interpret the latest scientific literature in the field, and design effective solutions to real-world problems in biomedical, social, and other domains.
Periodo di svolgimento
dal October 2025 a October 2025
Calendario
- 13/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra
- 15/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra
- 20/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra
- 22/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra
- 27/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra
- 29/10/2025 - 18:00/20:00 - Aula Beta, Ed. 24 – Piano Terra