Awarded Projects

Ammonia (NH3) is widely used in agriculture, fertilizer production and chemical industry. The process of commercial NH3 production relies on the Haber-Bosch process that is energy-intensive and highly dependent on fossil fuels, and has with significant greenhouse gas emissions.

This project proposes RegionReasoner, a reinforcement learning framework for region-grounded multi-round visual reasoning.

The first gravitational wave and electromagnetic (EM) observation of a merging binary neutron star (BNS) in 2017 demonstrated that such systems can launch powerful relativistic jets and, in turn, produce short gamma-ray bursts (SGRBs).

Cobalt (Co) is the key constituent of hard metal composites that are indispensable for advanced machining tools. Despite its use for over one hundred years, there is a strong interest in finding equivalent alternatives.

This project seeks to establish Linear Recurrent Neural Networks (LRNNs) as scalable and efficient alternatives to transformer-based Large Language Models (LLMs).

This proposal aims to support assessment of cloud feedbacks and climate sensitivity, as part of the the ongoing H2020 project Next Generation Earth Modelling Systems (NextGEMS).  Cloud response to climate change remains a primary uncertainty and challenge in future climate projection.

Galaxies and the gas surrounding them are turbulent and multiphase, i.e., colder (< 10^4 K) gas is embedded in a much larger, volume filling hot (≳ 10^6 K) phase, and regulates the fuel supply for star formation and black hole growth.

This project aims to leverage EuroHPC JU compute resources to advance AI-assisted debugging and self-correcting software systems through large-scale training and benchmarking of neural architectures for reverse execution and dynamic slicing.

This project aims to revolutionise the field of tabular data science, leading the foundation model revolution in this trillion dollar market.