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Massive Black Holes (MBHs) populate the centres of most, if not all, galaxies with total masses greater than approximately 1e12 solar masses.
This project makes use of a novel approach for numerical lattice simulations of the strong nuclear force.
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 proposes a Memory-Augmented World Model to improve long-horizon consistency in agentic decision-making and world prediction.
This project aims to study the turbulent flow over acoustic liners with a particular focus on the effect of Mach number.
MEVO is a project to train a domain-specific large language model from scratch for digital marketing advisory, campaign analytics, SEO, paid media optimisation, web development support, and multilingual business communication in Nordic markets.
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.