James Boyle
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Fertility, time to pregnancy, and pregnancy outcomes among women with recurrent miscarriages in the UK: a prospective observational longitudinal study
Koki C, Shields R, Sweetman R, Boyle J, Khan O, Lim Choi Keung S N, Arvanitis T N, Devall A J, Burroughs N J, Quenby S
Lancet Regional Health - Europe, June 2025, https://doi.org/10.1016/j.lanepe.2025.101343
Topological Data Analysis for Unsupervised Feature Selection in Large Scale Spatial Omics Data Sets
Boyle J, Hamm G, Williams E, JG Hartman R, Söderburg M, Henry I, Casey M (May 2025)
I am a stipendiary lecturer at Trinity College, where I teach the first and second year modules in probability and statistics.
I also teach/have taught intercollegiate classes for the following courses in the Mathematical Institute.
Academic year 2025/26:
- Tutor for B5.5 Further Mathematical Biology (MT)
- TA for B5.1 Stochastic Modelling of Biological Processes (HT)
Academic year 2024/25:
- TA for B5.5 Further Mathematical Biology (MT)
- TA for B5.1 Stochastic Modelling of Biological Processes (HT)
My work is funded by a Magdalen Graduate Scholarship.
I am interested in integrating mathematical modelling and machine learning to derive insights into biological and biomedical systems.
Machine learning is capable of picking up on the often very complex patterns in biological data, whilst mathematical modelling helps us understand what mechanisms might give rise to such patterns. My interest is in how we may combine these two paradigms to gain a richer insight into biological systems.
I am currently working on the development of deep learning tools for inferring cell-cell interaction dynamics directly from cell trajectory data.