Riccardo Cantini’s research spans two distinct areas: deep learning, focusing on Large Language Models (LLMs) and sustainable artificial intelligence, and big social data analysis, targeting politically polarized data and the efficient execution of data-intensive applications in high-performance distributed environments.
- Deep Learning and Large Language Models
- Big Social Data Analysis
Riccardo Cantini’s research in deep learning explores the potential of Transformer-based LLMs, such as BERT and GPT, showcasing their versatility across diverse domains. Sustainability is a central theme in this research area, emphasizing green awareness and promoting the efficient, fair, and trustworthy use of LLMs.
Riccardo Cantini’s research in big social data analysis explores how detailed user information from social media can be leveraged to uncover users’ perceptions of real-world events, offering data-driven insights into socio-political phenomena. His work addresses critical issues including reliability, language barriers, and dynamicity, while also tackling the challenges related to resource-intensive computation.
