Modeling; biomedicine; data science; late effect; machine learning

I specialise in data-driven research, using advanced computational techniques to identify, retrieve, classify and analyse data in order to generate hypotheses and develop models.

My primary interest is the modelling of human fertility, both for the healthy population and for survivors of childhood cancer.

I have industrial management experience and I am co-director of a charitable research foundation.

Future projects include the use of cheap and available bloodtest data to replace expensive and restricted PET scan results for children with cancer in developing countries; investigating the mental health outcomes for survivors of childhood cancer when compared to population controls; and using AI to individualise stimulation and trigger in IVF cycles.

My biomedical research is of direct importance to both healthy women (the accurate prediction of menopause is crucial when planning careers, relationships and pregnancies) and to survivors of childhood cancer (quantifying the effects of radio-and chemotherapy allows better treatment and more accurate advise and follow-up care).

PhD, School of Computer Science, University of St Andrews; MSc, Numerical Analysis & Programming, Dept. of Mathematics, University of Dundee; BSc, Mathematics, Heriot Watt University