Prof. Serge Guillas is investigating Environmental Statistics, and Uncertainty Quantification of complex computer models. Applications to tsunami and climate are carried out with his PhD students and a postdocs.

As Chair of the UCL- Met Office Academic Partnership, he supports multiple collaborations with researchers at the Met Office, and is currently interested in particular in the extension of weather and climate models using Data Sciences and Machine Learning: Uncertainty Quantification, Bayesian Calibration, Data Assimilation, with e.g. applications to upper atmosphere and cloud modelling. S. Guillas also collaborates with the UK Atomic Energy Authority (UKAEA) on modelling nuclear fusion, the clean energy of the future.

He is currently leading a project with the Universities of Exeter, Oxford and Warwick on Uncertainty Quantification of multi-scale and multi-physics computer models at the Alan Turing Institute. He also founded and leads the Uncertainty Quantification interest group of the Alan Turing Institute.

He has been leading multiple projects on tsunami risk for India, Indonesia, USA and Canada.