Rifa Punnota

I am a DPhil student supervised by Dr Ivan Koychev and Dr Vanessa Raymont. My research focuses on identifying multimodal neuroimaging (sMRI, DTI, fMRI, and PET) and blood-based (proteomic and epigenomic) biomarkers that capture resilience and risk across the Alzheimer’s disease spectrum, with the aim of improving diagnosis, prognosis, and risk stratification. My project integrates large-scale multimodal data using deep learning, transformer-based architectures, and multiomic foundation models to uncover cross-modal patterns that enhance biomarker discovery, disease prediction, and prognostic trajectory modelling. My DPhil is funded by an Oxford-MRC iCASE studentship and is in close collaboration with my industrial partners, Prima Mente. 

Prior to starting my DPhil at Oxford, I completed my MSc in Computational Neuroscience at Imperial College London. My MSc project focused on integrating multimodal neuroimaging using machine learning approaches to investigate the predictive utlity of key biomarkers of Alzheimer's disease within different stages across its trajectory. Following my MSc, I worked as a Research Assistant and Clinical Trial Coordinator at Imperial, where I contributed to several observational, commercial, and clinical studies in dementia research. Earlier, I completed my BSc in Pharmacology, with a strong focus in Neuroscience, from University College London (UCL), where I completed my final year research project on investigating molecular markers of epilepsy.