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Detailed Program


The school is organized in two parts: in the morning students will attend lectures with different speakers, while in the afternoon they will work on group projects guided by dedicated tutors.


TIME

Sunday 21

Monday 22

Tuesday 23

Wednesday 24

Thursday 25

Friday 26

09:00 09:30

Meeting the Tutors

Registration

09:30 10:00

Round of presentations (Students)

Sara Colantonio
AI and Health

Alessio Rossi
Sport Analytics on Football

Jose Such
Human-centred AI Privacy

10:00 10:30

Roberto Trasarti
SoBigData RI & School Introduction

Projects Presentations
chaired by Mark Coté

10:30 11:00

Valerio Grossi
Tutorial SoBigData Lab

11:00 11:30

Coffee Break

Coffee Break

Coffee Break

Coffee Break

Coffee Break

11:30 12:00

Project Challenges Presentation
by Francesco Oleni, Matteo Marescotti, Giuseppina Sgandurra, Pietro Ilio Gatti

Elena Cardillo
Healthcare Data and Knowledge Representation

Maurizio Napolitano
Volleyball Analytics

Francesca Naretto
Privacy, Fairness and XAI

Projects Presentations
chaired by Mark Coté

12:00 12:30

Salvatore Rinzivillo
Visualization Health

12:30 12:45

Elisabeth Black
Agentic AI

Awais Rashid
Data Protection

12:45 13:30

Vasiliki Voukelatou
Wellbeing

13:30 15:00

Lunch Break

Lunch Break

Lunch Break

Lunch Break

Lunch Break

15:00 16:00

Developing Student Projects with Tutors

Developing Student Projects with Tutors

Free Afternoon

Developing Student Projects with Tutors

Internal Meeting
SoBigData RI

16:00 16:30

Coffee Break

Coffee Break

Coffee Break

16:30 18:00

Developing Student Projects with Tutors

Developing Student Projects with Tutors

Developing Student Projects with Tutors

18:00 20:30

Welcome Cocktail
and dinner

Social Event
Petra winery tour and dinner

20:30

Dinner
Serata Toscana

Dinner
Serata Mare

Social Event
Pizza and DJ set

Daily Program


The opening day introduces participants to the SoBigData Research Infrastructure, providing a clear overview of the tools, services, and opportunities it offers to the research and data science community. Experts will present how SoBigData supports interdisciplinary research and fosters collaboration across domains. The day also features presentations from companies and associations that will outline real-world social challenges. These case studies will serve as inspiration and starting points for the group projects that participants will develop throughout the summer school, helping to ground the technical work in concrete societal needs.

The second day focuses on the rapidly evolving intersection between artificial intelligence and healthcare, with particular attention to personal wellbeing and the responsible use of health data. Participants will explore how data analysis and visualization techniques can be applied to understand health trends, support clinical decision-making, and promote preventive care. Through expert lectures and practical examples, the sessions will highlight both the opportunities and the challenges of working with sensitive health information, emphasizing methodological rigor and ethical awareness.

This day is dedicated to data-driven approaches in sports and the emerging paradigm of agentic AI. Participants will learn how advanced analytics can be applied to domains such as soccer and volleyball, including performance analysis, tactical evaluation, and injuries prediction. In parallel, the concept of agentic AI will be introduced, focusing on systems capable of autonomous or semi-autonomous decision-making. By combining sports case studies with AI methodology, the day provides a dynamic environment to understand how intelligent systems can support complex, real-time analytical tasks.

This day addresses the critical themes of privacy, security, fairness, and responsibility in data science. Participants will examine the ethical and legal requirements involved in collecting, processing, and modeling data, with special attention to possible mitigation, transparency, and compliance with data protection regulations. Through lectures and discussions, the sessions will emphasize best practices for building trustworthy and socially responsible AI systems. This concluding theme encourages participants to integrate ethical reflection into every stage of the data science pipeline, reinforcing the importance of responsible innovation.

The final day of the summer school is dedicated to the presentation of the projects developed by the participants throughout the week. Each group will have the opportunity to showcase their work, demonstrating how they applied the methodologies learned to address the real-world challenges proposed by the partner companies and associations. The presentations will be followed by feedback sessions, where experts and peers will provide constructive insights. The day will conclude with closing remarks that reflect on the key takeaways from the program and outline future opportunities for collaboration and research within the SoBigData community.