Multimodal AI

Utilizing advanced artificial intelligence to process multimodal data to enhance the diagnosis and prognosis of Parkinson’s Disease, paving the way to uncover the underlying mechanisms of Parkinson’s Disease and improve its prediction.

Using digital databases and advanced AI to predict new, sustainable materials for green technologies, accelerating the shift towards net-zero emissions and driving substantial progress in global sustainability initiatives.

Exploring innovative methods to optimize AI models using multi-fidelity data, aiming to enhance accuracy and efficiency across engineering disciplines by leveraging diverse data sources to improve model performance while reducing reliance on high-cost precision data.

Harnessing advanced AI technology to discern novel biomarkers, paving the way for enhanced chronic nerve pain treatments and revolutionising healthcare outcomes.

Leveraging deep learning to refine OCR transcriptions of the extensive British Library Newspapers collection to overcome the barrier of inaccurate text data, unveiling a rich resource for exploring centuries of historical narratives and advancing global humanities research.

Utilising advanced AI to process multimodal cardiothoracic data for enhanced diagnosis and prognosis of Cardiothoracic Disease (CTD), paving the way for personalised medical care and transformative approaches in heart and lung health.