Ruby Wood
CDT Student
I have an MMath from the University of St Andrews. My Masters dissertation was on comparing classical clustering approaches with Bayesian partitioning techniques. During my undergraduate studies I undertook a couple of data science internships, one of which involved clustering cancer patient data. After graduating I trained and then worked as a software engineer for two years, at a multinational investment bank, using mostly Java. I also did some machine learning within this role. I am funded by Cancer Research UK. Away from studying I enjoy squash, running and yoga.
Recent publications
-
Self-interactive learning: Fusion and evolution of multi-scale histomorphology features for molecular traits prediction in computational pathology.
Hu Y. et al, (2025), Medical image analysis, 101
-
Quantitative analysis of bone marrow fibrosis highlights heterogeneity in myelofibrosis and augments histological assessment: An Insight from a phase II clinical study of zinpentraxin alfa.
Ryou H. et al, (2024), HemaSphere, 8
-
Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy.
Lafarge MW. et al, (2024), NPJ precision oncology, 8
-
Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology Images
Wood R. et al, (2024), IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 5122 - 5131
-
Enhancing Local Context of Histology Features in Vision Transformers
Wood R. et al, (2022)