Thanks to the generous support provided by the Big Data Research Infrastructure’s Transnational Access (TNA) program, I had the incredible opportunity to carry out a portion of my research at one of the prestigious nodes of the SoBigData Research Infrastructure, located in Tartu, Estonia. 

This program opens doors for researchers like me to collaborate with world-class experts, access cutting-edge technologies, and push the boundaries of big data research. Reflecting on my time there, I can confidently say it was a transformative experience.

Data structures are part of the backbone of all data systems, data analytics and machine learning pipelines. These crucial components carefully organise information to make it efficiently accessible and usable by algorithms and applications, thus accelerating their performance and facilitating the discovery of new insights from data.

The third edition of ITADATA Conference (https://www.itadata.it/), organized by the CINI Big Data National Laboratory and ISTI CNR,  kicked off successfully on September 17th. This three-day event is dedicated to exploring the latest advancements in big data and data science.

The first day of ITADATA2024 was jam-packed with activities. It began with the thrilling finale of the ITADATAHack, where teams showcased their innovative solutions.

This past summer, I had the privilege of being one of the Transnational Access (TNA) visitors at the Universitat Rovira i Virgili (URV) in Tarragona. I was invited by Dr. Josep Domingo-Ferrer to collaborate with his esteemed team in the CRISES Lab. 

On July 2024, using the TNA program of the SoBigData project, I visited the prestigious King’s College of London, UK, and worked with prof. Mohammad Reza Mousavi and his staff on topics regarding quantum computing algorithms and their possible application to the problems of the modern society, e.g., smart cities and cyber-physical systems.

During my TNA visit at KTH Royal Institute of Technology, we pursue the task of designing efficient algorithms to solve combinatorial optimisation problems with algorithmic fairness in perspective. It has been observed that algorithms designed solely for optimising the cost–to maximising profits–can exhibit inherent bias in their decisions, particularly towards certain groups of the society such as women and people of colour [1]. Using software systems with inherent bias is questionable and many legislations prohibit deploying systems known to exhibit bias.

Sheffield is a city of tailored made tools. Renowned for its steel craftsmanship, it was apparently once hailed as the steel-making capital of the world and even boosted in the Canterbury Tales for its cutlery-making. No pair for scissors will top the ones you can still until this day get in Sheffield, although customers are warned waiting time can take up to ten weeks for them to be ready for delivery. 

Hi, my name is Maxime and I had the pleasure to do an internship at the Scuola Normale Superiore in Pisa on the modelization of decentralised exchanges based on stochastic processes. I am French and for two months I lived in Pisa to have a foreign experience in research.

LEGISLATIVE BACKGROUND

The emergence of artificial intelligence in the educational context presents great opportunities, but also poses unprecedented challenges. The European Union introduced the AI Act (EU Reg. 2024/1689) to establish a common regulatory framework, ensuring the safe and reliable use of AI systems. The key points relating to education are: