From the emergence of stable cooperative communities to the rapid spread of antimicrobial resistance, evolution shapes the biological world in profound ways. By developing and analysing mathematical models, we aim to understand the forces that govern population dynamics, species interactions, and evolutionary change over time scales from weeks to millions of years.

Our work integrates concepts from ecology, evolutionary theory and population genetics to explore how complex biological systems adapt and persist.

Mathematical approaches

Graphic showing states of human evolution — Our work examines some of the core questions of evolution.

We construct deterministic and stochastic models of inter- and intra-specific interactions to capture key evolutionary mechanisms. Our frameworks include population genetics, quantitative genetics, game theory, adaptive dynamics, and dynamical systems models. Analytical approaches are complemented by numerical simulation and statistical analysis to explore outcomes under realistic biological conditions.

Applications

Our research explains how sexual reproduction can evolve, why cooperation is often maintained in nature, and how host-pathogen interactions shape virulence evolution and the flexibility gene-regulatory networks. We have investigated the mechanisms driving speciation and biodiversity, and explored how environmental variability influences ecological stability. Collaboration with experimental biologists ensures that our theoretical insights are grounded in empirical reality.