Doctoral Researchers Outline Latest Thinking on Big Data and Environmental Risk

Environmental laboratory

Doctoral Researchers Outline Latest Thinking on Big Data and Environmental Risk

03 Apr, 2018

Published over 8 years ago. See the latest and most current information on Environmental laboratory.

The DREAM-CDT (Data, Risk and Environmental Analytical Methods - Centre of Doctoral Training) recently held its annual symposium at Cranfield University.

Forty Doctoral researchers from Cranfield, the University of Cambridge, Newcastle University and the University of Birmingham gathered to discuss their latest research findings around how to use ‘big data’ to mitigate environmental risk.

Topics discussed at the symposium covered a number of scientific themes, from advanced visualisation of risk, analysis of social media to predict spread of infectious disease, to the use of remote sensing to detect climatic risk to the built environment and flood mitigation at city scale. Students also heard presentations from expert practitioners keynote speakers and a range of industry delegates were also able to exchange ideas with the students at the event.

The DREAM-CDT is a multi-million pound investment from the Natural Environment Research Council (NERC) and the Economic and Social Research Council (ESRC) and aims to fill the UK skills gap in environmental data science by providing funded PhD studentships. A further cohort of students have also been recently added, associated with the National Productivity Investment Fund linked to the UK Government Industrial Strategy.

Dr Stephen Hallett from Cranfield University and Director of the DREAM-CDT, said: “This symposium provided a great opportunity for early-career researchers to get together to present their latest research findings and to hear from industry leaders.

“In our increasingly digital world, ‘big data’ is becoming ever more important to business and society. Collected by devices from mobile phones to unmanned aerial vehicles, and from satellite remote sensing devices to embedded sensor networks, the datasets can become so large and complex that it becomes difficult to apply traditional data processing applications to analyse them.

“There is a tremendous opportunity to harness this ‘big data’ to mitigate environmental risks. It was fantastic to see the DREAM researchers embracing this challenge and developing their ideas and thinking with their peers.”

IET 36.2 Mar/Apr 2026

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