Awarded Projects

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.

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.

The project proposes to better understand the fueling of supermassive black holes from galactic scales using multi-scale numerical modelling.

MultiCellFM aims to develop an advanced Cell Foundational Model (CFM) that leverages cutting-edge artificial intelligence to extract meaningful insights from vast single-cell datasets.

The project team proposes a suite of multilingual continual pretrained Dense and Mixture-of-Expert (MoE) models at different size tiers for different types of workloads that have different inference compute constraints.