Extreme Value Theory for Early Warning Systems


Going extreme for forecasting

Classical statistical methods have limitations for characterising extremal behaviour which is of particular interest when we study natural hazards such as volcano eruptions and floods. Just as extreme value models have been used for financial risk forecasting, we seek to build extreme value models to better inform early warning systems.

This project is joint work with Prof. Almut Veraart of Imperial College London and Assoc. Prof. Benoit Taisne of Earth Observatory of Singapore, and supported by the Nanyang Technological University – Imperial College London collaboration grant.

EOS Annual Meeting 2022 Poster

An overview of research progress as presented to members of the Earth Observatory of Singapore (EOS). 


Student engagement activities

Under our collaboration grant, we brought together motivated undergraduate students from Imperial College London as well as Nanyang Technological University to join us in our research on extreme value and spatial methods for environmental risk modelling. 

Our Team

Michele Nguyen


Almut Veraart


Benoit Taisne


David Lallemant