Awarded Projects

The project focuses on creating Video-Based Language Models (VBLMs) that can precisely identify, measure, and categorize operator movements within manufacturing environments.

By employing transformer neural networks, the model aims to learn fundamental properties of protein sequences directly from mass spectra data.

This project will perform cross-datacenter training of a stage-of-the-art multilingual LLM at an unprecedented scale (tens of billions of parameters trained on tens of trillions of tokens) using coordinated allocations across multiple supercomputers.

The primary aim of this project is to develop large-scale brain-like machine learning algorithms.

Vision language models (VLM) represent a multimodal extension of text-based language models that allow to incorporate visual information into the generation process of the output text.

This project aims to develop a unified, diffusion-based video generation framework capable of synthesising high-fidelity human avatars with generalisable fine motor control and physical interaction capabilities.

This proposal portrays several extensions to this discovery, which involve optical manipulation of the laser beam to achieve brighter radiation beams. The main strong-suit of the proposed research is that it is closely followed by experiments using our 20 Terawatt (TW) laser lab.

The free-surface flow induced by progressive non-breaking wind waves propagating in shallow waters over a  horizontal bottom will be investigated by means of Direct Numerical Simulations (DNS).

This project aims to construct a comprehensive map of drag reduction as a function of Reynolds number and verify the reliability of finite-Reynolds-number extrapolations.