Emma Walker
CDT student
Emma is a third-year DPhil student in the Nellaker Group at the University of Oxford's Big Data Institute (EPSRC CDT in Health Data Science), where she works with a focus on computational pathology. Her research centres on the quantitative analysis of placental histology, with the aim of transforming subjective pathological assessment into objective, reproducible characterisation with clinical prognostic applications. She is helping develop HAPPY (Histology Analysis Pipeline.PY), a bottom-up computational pipeline.
She previously undertook a MSci in Natural Sciences at the University of Exeter with her master's project focusing on computational neuroscience, and how to design artificial neural networks inspired by the human brain.
Broadly she is interested in developing machine learning models to understand human health trajectories and pursuing this research within women's health.
Recent publications
AI-assisted placenta pathology in clinical use: barriers and opportunities.
Journal article
Walker EC. et al, (2026), Placenta
Biologically inspired digital histology for deep phenotyping of placental composition changes across major lesion types.
Journal article
Walker EC. et al, (2026), Placenta
Biologically Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types.
Preprint
Walker EC. et al, (2025)
Navigating Severe Class Imbalance in Population Cohort Data.
Conference paper
Fieggen J. et al, (2025), Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2025, 1 - 6