Matthew Piggott

Professor Matthew Piggott is a distinguished academic at Imperial College London, holding the Chair in Computational Geoscience and Engineering within the Faculty of Engineering. His research bridges interdisciplinary engineering, mathematical sciences, and environmental data science, with a focus on renewable energy systems, computational fluid dynamics, and geophysical modeling. He leads the MSc Environmental Data Science & Machine Learning program and contributes to initiatives like the Energy Futures Lab and Grantham Institute.

• Education: PhD in Mathematics (University of Bath, 2002), MMath in Mathematics (University of Bath, 1998)
• Academic Positions: Professor (2016–present), Reader (2008–2016), Research Fellow (2005–2008)

Piggott's research integrates mathematical modeling, machine learning, and high-performance computing to address environmental challenges. Key areas include flood forecasting, tidal and wind energy optimization, coastal change analysis, and geophysical fluid dynamics. His work leverages advanced numerical methods, data assimilation, and mesh adaptation techniques for applications in climate science and marine engineering.

Recent publications highlight his expertise in data assimilation (e.g., latent 3D-Var, 4D-Var), machine learning for environmental flows, and renewable energy system design. His team employs convolutional autoencoders, graph transformers, and deep learning to model unstructured grid data, optimize wind farms, and assess climate impacts on small island nations. Articles also emphasize mesh adaptation for ice flow and tidal turbine arrays, remote sensing for marine hydrodynamics, and multi-fidelity transfer learning for wake modeling.

As a member of the Applied Modelling and Computation Group, Ocean Plastic Solutions Network, and Data Science Institute, Piggott collaborates across disciplines. His work often involves Firedrake and PETSc frameworks, with applications in tsunami risk assessment, microbial patchiness, and rock coast evolution. Current projects address offshore wind wake losses, tidal turbine economics, and climate change mitigation through computational methods.