Awarded Projects

Fluid mechanics are fundamental to collective behavior in nature and technology ranging from fishschools to wind farms.

LetzAI is a generative AI platform designed with a clear purpose - to give individuals, artists, and brands control over how they are represented in an AI system.

Leveraging high quality internal data of the European Institutions at scale to build an EU institutional large language model (LLM)

This proposal centers on investigating two primary research questions:

(i) the influence of Reynolds number on rough-wall turbulence, emphasizing inner/outer region interactions, and

(ii) the effects of wall curvature and its interplay with pressure gradients.

Computer-aided drug design can significantly reduce the time and resources needed for drug discovery because experimental high-throughput assays can be replaced with virtual screens.

CAD files are widely used in manufacturing sectors such as automotive, aerospace, and construction. Traditionally, these CAD files are archived as images, making it difficult to retrieve structured information.

By replacing isolated task-specific models with a shared representation and natural-language analytical interface, the project aims to reduce expert-driven processing and accelerate GC×GC–ToF-MS research across forensic, environmental, biomedical, and industrial applications.

The project aims to obtain a new state-of-the-art in both ML parameterisation and stochastic parameterisation, with the potential to significantly reduce and better characterize model uncertainty in both weather and climate models.

This project leverages advanced Machine Learning techniques, specifically Neural-Network Quantum States optimized via natural-gradient methods and neural importance sampling, to resolve the ground-state and low-energy properties of the anisotropic triangular-lattice Hubbard model.