Rafael de Oliveira Silva

The world is more probabilistic than predictable, writes US statistician Nate Silver in his 2013 book The Signal and The Noise: The Art and Science of Prediction, yet maths teachers tend to “spend more time on abstract subjects like geometry and calculus than they do on probability and statistics.” We all know that predicting the future is very difficult, to borrow Danish physicist Niels Bohr’s droll expression, so perhaps we should be paying more attention to mechanisms for working with probability if we want to know what might happen in some of the big challenges we face, such as our ability to produce sufficient food on a sustainable basis.

Rafael de Oliveira Silva would agree. A Chancellor’s Fellow at the University’s Global Academy of Agriculture and Food Security, he’s an applied mathematician working with mathematical models of agriculture, food security and biodiversity conservation. “Mathematical modelling is the only reliable tool we possess to ‘predict’ the future,” he says. “By using math equations to represent the functioning and interactions of complex food systems, we can predict what’s expected to happen in future climate scenarios, and how best to address those challenges under pre-defined assumptions and simplifications.” His research includes modelling climate change adaption and the social impacts of sustainable intensification pathways, the energy-livestock-deforestation nexus, and optimising cryogenic conservation of livestock genetic resources. These may sound like abstract concepts too, but they can have a critical impact on everyday life.

A global challenge like climate change can seem too big and complex for individuals to be able to affect, despite the inspiring efforts of young activists like Greta Thunberg. But Dr de Oliveira Silva believes mathematical modelling of issues such as food security and biodiversity conservation can be used to empower us all; “Mathematical modelling can help decision makers, from policy makers to consumers, take better-informed decisions to minimise the negative impacts of climate change.”

He views the Chancellor’s Fellowship as an opportunity that provides the necessary support for early career researchers to develop leadership in their chosen topic and become independent researchers. And he is confident that Data-Driven Innovation is a powerful means of providing support to the whole City Region. “DDI means applying innovative mathematical and computational methods to effectively use large data sets, across the economy,” he explains. “DDI can extract unique information and solutions for a variety of socio-economic and environmental problems faced by Edinburgh and South East Scotland’s public and private sectors.” Is that a prediction? Probably.

Image of Rafael de Oliveira Silva
Rafael de Oliveira Silva is a DDI Chancellor's Fellow

By using math equations to represent the functioning and interactions of complex food systems, we can predict what’s expected to happen in future climate scenarios, and how best to address those challenges

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