Awarded Projects

The goal of this project is to design a framework that unifies multiple video grounding tasks. The aim is to develop a video-language model flexible to take different type of inputs and produce different type of outputs for various spatio-temporal grounding problems

Investigation of processes at nanosurfaces is highly challenging since atoms in the bulk typically dominate the signal measured in experiments, and here molecular ab-initio level simulations can produce valuable information.

Abkarino is a domain-specialised, text-only AI foundation model for computational chemistry. It supports day-to-day work in organic, inorganic/non-organic, and physical chemistry while natively integrating regulatory and compliance reasoning.

The main goal of this computational project is to compute, from first principles lattice QCD simulations, the quark-gluon vertex, in both Landau gauge and in linear covariant gauges.

In the context of aeronautics and air transport, the industry has to face new challenges regarding performance and sustainability.

This project proposes a refined framework for automated, efficient, and transferable dataset generation called Smart Configuration Sampling. SCS employs active learning strategies, utilizing ensemble model deviations to guide the iterative selection of high-value atomic configurations.

Colloidal Quantum Dots (QDs) are nano-sized crystallites notable for their exceptional semiconductive properties, which were recently acknowledged with the Nobel Prize in Chemistry.

This project focuses on the design of lipid nanoparticles (LNPs) for efficient RNA-based therapeutics delivery, addressing critical challenges in the field.

Radiotherapy (RT) is one of the most frequently used methods for cancer treatment (above 50% of patients will receive RT).