Daniel Tweneboah Anyimadu

I am a PhD researcher in Computer Science at the University of Exeter, working at the intersection of artificial intelligence (AI), medical imaging and healthcare. My research focuses on developing AI-based methods for low-field MRI reconstruction and super-resolution, with the aim of recovering fine image detail, improving visual quality and supporting more reliable and clinically useful diagnostic imaging.

Before beginning my PhD, I received a BSc in Biomedical Engineering from the University of Ghana in 2021, where I developed foundational skills in biomedical instrumentation, physiological signal processing, data analysis, programming and healthcare technology. I subsequently completed the Erasmus Mundus Joint Master’s degree in Medical Imaging and Applications (MAIA) in 2024, studying at the University of Girona in Spain, the University of Burgundy in France, and the University of Cassino and Southern Lazio in Italy. During the programme, I undertook my master’s thesis research as a Visiting Scientist in the Department of Biomedical Engineering and Imaging Sciences at King’s College London (KCL), further strengthening my expertise in medical image processing, machine learning, data curation and interdisciplinary research.

My broader research interests include medical image analysis, particularly image reconstruction, super-resolution, image quality transfer, classification, segmentation and registration, as well as computational imaging, uncertainty quantification, causal machine learning and AI-driven diagnostic systems. Through my doctoral research, I aim to develop reliable, generalisable and clinically relevant AI methods for medical imaging.