Awarded Projects

Adding polymers to a Newtonian solvent alters the turbulence, ultimately resulting in the macroscopic effect of drag reduction (DR) in a turbulent wall-bounded flow.

This project aims to study the turbulent flow over acoustic liners with a particular focus on the effect of Mach number.

The objective of the project is building the next-generation version of the first pre-trained Italian LLM: Minerva 2.

Mitochondrial diseases result from defects in oxidative phosphorylation caused by mutations in genes in the nuclear and mitochondrial DNA. These mutations produce a wide range of abnormalities and symptoms that can make an accurate diagnosis difficult.

This project addresses the growing need for accurate information retrieval in light of challenges posed by large language models (LLMs) like ChatGPT, which can produce misleading content through a phenomenon known as hallucination.

Information Retrieval (IR) is crucial for search engines and knowledge discovery, yet current methods struggle with the trade-off between effectiveness and efficiency.

By facilitating early toxicity screening and optimization, ModTox aims to enhance the success rates of drug development while minimizing costs and time investments.

Natural language processing (NLP) has seen tremendous progress recently through the use of complex neural network models that learn effectively from very large amounts of data, but the use of data-intensive large-scale models also gives rise to challenges.

Understanding if VUS affect proteins and their impact at the molecular level is crucial for expanding our knowledge of cancer, developing personalized prognosis and treatments, or assisting genetic counseling.