I am an environmental data scientist who uses mathematical modelling, combining statistical, mechanistic, and machine learning approaches, to understand how climate and land use change affect ecosystem health, biogeochemical cycles, and species interactions from molecular to global scales. My research lies at the intersection of ecology, chemistry, and mathematics and is inherently multidisciplinary. I typically work in aquatic systems, both marine and freshwater.
A central focus of my work is capturing variability and extreme events, including hazards such as harmful algal blooms, floods, or environmental pollution. I use distributional regression frameworks to move beyond average responses, linking environmental drivers to both typical and extreme ecosystem outcomes.
As a member of the global GAMLSS (Generalized Additive Models for Location, Scale, and Shape) network, I am contributing to probabilistic modelling approaches that quantify uncertainty, variability, and ecological risk.
