My pronouns are he/him
My research focuses on the mechanisms that drive change in natural systems, integrating ecological and evolutionary dynamics through mathematical and computational approaches. I pursue this through three main research directions:
- Ecological dynamics and ecosystem functioning. I develop and analyse mathematical models (including IBMs, ODEs, PDEs, and IPMs) to study the dynamics of complex terrestrial and aquatic systems. My work examines top-down and bottom-up processes in systems such as Yellowstone National Park, as well as freshwater communities across France, with a particular emphasis on the effects of climatic and anthropogenic stressors on ecosystem structure and stability.
- Evolutionary dynamics in natural populations. I model adaptive processes and their interaction with ecological dynamics, using systems such as Trinidadian guppies and datasets from Darwin’s finches. This work aims to identify the drivers of phenotypic change and understand how evolutionary processes feed back on population dynamics and on the wider ecosystem.
- Methods at the interface of mathematical modelling and machine learning. I develop approaches that combine mechanistic models with deep learning, including work on Neural ODEs and neural network extensions of structured population models. These methods aim to better capture complex biological processes, such as genotype–phenotype relationships.
More recently, I have begun developing computer vision approaches to extract phenotypic information from standardised imagery. I apply these methods both to natural systems and to digital pathology, with the goal of quantifying phenotypic dynamics and understanding evolutionary processes in disease, such as cancer, museum collections and wild populations.
