Data Science

We use AI and data science throughout out research, from materials discovery to space weather.

We are developing and applying machine learning techniques for understanding space plasma phenomena and forecasting space weather events using physics-informed approaches to machine learning, both to improve the current forecasting capability of space weather, but also to unveil new physics more generally from data.

Our researchers combine advanced physical understanding of molecular interactions with machine-learning to find solutions to problems of importance in healthcare, energy and the environment, as well as basic science.

 Using data science techniques initially developed to analyse particle physics experiments, we analyse the relationships between traffic and air quality. A first example of this analysis was  applied to pollution measurements and traffic intensities from Mexico City.