Type and Duration
Preproposal PhD-Thesis, since September 2024Coordinator
Data Science & Artificial IntelligenceDescription
The research explores the application of AI-driven sequence data analysis in two healthcare areas: blood group antigen characterization and enhancing intelligent upper limb prosthetics. The first study explores how AI models can improve our understanding of blood group antigens. The goal is to identify and understand changes in antigenicity caused by mutations to reduce adverse reactions during blood transfusions, thereby improving maternal and foetal health outcomes and enhancing healthcare efficiency.The second objective is centred on improving the reliability and functionality of upper limb prosthetics. This shall be achieved by integrating multimodal data, including electromyographic signals from residual limbs and speech commands. The research aims to create a more intuitive and effective control mechanism for prosthetic devices, ultimately enhancing the user experience and promoting social and workforce inclusion for individuals using prosthetics.
This research seeks to identify cross-domain methodologies and algorithmic synergies to drive innovation in healthcare through generative AI and advanced machine learning models. Combining insights from protein structure prediction and prosthetic control, the research seeks to contribute to personalised medicine and intelligent assistive technologies, pushing forward innovation in healthcare applications.
