Machine Learning for Environmental Sciences 2019

The British Antarctic Survey and the University of Cambridge are hosting a 2 day (lunch-to-lunch) workshop on Machine Learning for Environmental Sciences, to be held at the British Antarctic Survey on Monday 17th to Tuesday 18th June.

An improved understanding of the natural environment and ability to predict future changes is crucial for society and the global economy. With ever growing volumes of data produced through both increased environmental modelling capability and technological advances in earth observation systems, techniques to harness the power of this data and extract useful information have never been more important. Recent years have seen an acceleration in the use of Data Science techniques being applied within the environmental sciences. The application of Machine Learning to this new area has also identified a number of new and interesting challenges to the data science community, with new data challenge requiring bespoke machine learning tools to deliver the next wave of scientific breakthroughs.

This conference follows on from the 2017 conference on “Environmental Science in the Big Data Era” hosted by BAS and the University of Cambridge and aims to bring together Machine Learning engineers and Environmental Scientists who are active in this area, with a view to establish new collaborations and strengthen existing networks. In particular we encourage Early Career Researchers to attend and offer a limited number of reduced price tickets for ECR’s (researchers within 10 years of their most recent degree).

The workshop will feature a keynote talk from Claire Monteleoni (University of Colorado), as well as presentations on both recent achievements and proven concepts in the area, and more preliminary work and results.

Following the workshop we will host a ‘Hands-on Data Challenge’ session on the afternoon of Tuesday 18th following lunch, featuring practical examples of Machine Learning applied to Environmental Data Sets. The session is open to everyone and aimed at all levels of expertise. Please provide your own laptop, and we will provide access to suitable datasets and ensure expert support is available.

For more information and to register please visit