School of Computing and Mathematical Sciences

Mathematical and computational modelling for natural sciences and engineering

The research performed in the group of Mathematical and computational modelling for natural sciences and engineering aims at creating new accurate and efficient models for simulating a variety of natural, engineered, and conceptual systems. We investigate specific problems as well as address general questions in complex systems, with the key goal of advancing interpretability and prediction. We focus on the study of the emerging area of Mathematics of Planet Earth, by developing new frameworks for understanding and predicting the behaviour of the climate systems and ecosystems across multiple scales, thus aligning with the research devoted to supporting the achievement of multiple Sustainable Development goals. We develop new algorithms for performing model reduction also in absence of clear time scale separation between the dynamics of interest and the unresolved scales. We also perform research aimed at improving our understanding of complex materials for a variety of applications.

Research expertise

  • Nonequilibrium Statistical Mechanics
  • Data-driven Methods and Machine Learning
  • Mathematics of Planet Earth
  • Computational Physics
  • Rare event algorithms
  • Extreme Events
  • Levy Processes
  • Critical Transitions
  • Geophysical Fluid Dynamics and Climate Dynamics
  • Ecosystem Modelling
  • Population Dynamics
  • Mathematical Biology
  • Spatial Ecology
  • Digital Agriculture
  • Multiagent Systems
  • Nanoparticles
  • Material Science
  • Nonlinear Optics
  • Granular Matter
  • Neural Networks
  • Koopmanism

Group members

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