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Dr Drew Purves

Dr Drew Purves

Research Scientist,

Google DeepMind, based in London


Biography:

Drew has 16 years’ experience in ecological and environmental modelling, data analysis and data visualization and he has just started working for Google DeepMind.

Between 2007 and October this year, he was the head of the Computational Ecology and Environmental Science group (CEES), a unique group of ecologists sitting within Microsoft Research in Cambridge. Under his leadership, CEES adopted a mission to (1) develop new predictive models of different aspects of the Earth System, and (2) create new algorithms, methods and prototype software tools to enable this kind of modelling. The group carried out a wide variety of original ecological research, focussing on predictive modelling of global-scale environmental phenomena (e.g. the carbon cycle, biodiversity, agriculture); and packaged these results into software tools which they shared, freely.

While he was there, his research spanned many questions, taxa and scales, ranging from studies of the growth and development of small plants measured over a few days, through studies of how the continental-scale geographical distributions of tree species emerge over timescales of centuries; to global-scale models of carbon, biodiversity, and ecosystem function. However, this otherwise broad research 'programme' is united by an insistence on adopting a 'joined up' approach to ecology -- marrying models, with data, via comptutational statistics, in order to provide defensible, believeable models of ecological phenomena. Developing such models both increases our understanding of nature, and provides the ability to manage it better. At Microsoft, he had a green light to pursue this research agenda, whilst packaging up the various novel software that it requires into reuseable tools in order to allow other scientists to more easily adopt the same joined up approach to ecological modelling.

Before going to Microsoft, he did a post-doc at the Department of Ecology and Evolutionary Biology at Princeton, a PhD at the University of York and Plant Sciences at Cambridge.

Keywords

  • ecological and environmental modelling
  • data analysis and data visualization
  • biodiversity conservation