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Personal profile

Profile Keywords

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

Research overview

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.

Research interests

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

Other expertise

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

Future research

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.

Industrial relevance

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).

Academic/Professional Qualification

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

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

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Collaborations and top research areas from the last five years

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