I have been an assistant professor and research fellow at the University of Nottingham for one year, having just finished my PhD in statistics last November.
Throughout my PhD I became very interested in the role of tech within statistics, particularly big data. Big data is becoming increasingly common and powerful to use, however big data presents computational and speed problems that we need increasingly sophisticated tech to deal with. I particularly focused on network data in my Thesis, but alongside my PhD I became a research assistant implementing state of the art machine learning methods to large health datasets.
My research currently is on the grant ‘ Risk prediction for Women’s Health and Rights in Tanzania: novel statistical methodology to target effective interventions’. I have been involved in working with the digital global health company Dtree in Zanzibar to use individuals maternity data, collected with mobile phones, to predict instances of perinatal mortality. The aim of this work is that Dtree can then implement interventions based on the predictions we create. I am currently also working with ‘Hope for girls and women’ a safe house in Tanzania for girls at risk of Female genital mutilation(FGM), a human rights violation, we hope to create mobile surveys to collect data on FGM occurrences and use novel statistical and machine learning methods to feed in to interventions. I am very passionate about this work and am happy I get to combine technology and statistics for such worthwhile causes.
Within my role as assistant professor I also lecture a machine learning module. There is a real emphasis in this module on coding in this module that I really enjoy teaching. The power of being proficient in coding is becoming so important in many careers our undergraduates will go into and so helping teach it is very rewarding.
