Matthew Piggott

Matthew Piggott

Imperial College London

H-index: 42

Europe-United Kingdom

About Matthew Piggott

Matthew Piggott, With an exceptional h-index of 42 and a recent h-index of 28 (since 2020), a distinguished researcher at Imperial College London, specializes in the field of Computational Science, Data Science, Computational Fluid Dynamics, Offshore Renewable Energy, Coastal Hazards.

His recent articles reflect a diverse array of research interests and contributions to the field:

An unsupervised learning approach for predicting wind farm power and downstream wakes using weather patterns

Latent Neural Mapping for Hydrological Data Assimilation in Flood Prediction

Tidal turbine array modelling using goal-oriented mesh adaptation

Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series

Measuring Marine Hydrodynamics from Space Using Planet Satellite Imagery

Applications of Data Assimilation and Parameter Calibration with Multi-Resolution Measurements of Seawater Temperature for Hydrodynamic Modeling of Shallow, Tidal Environments

Nearshore tsunami amplitudes across the Maldives archipelago due to worst-case seismic scenarios in the Indian Ocean

Learning to optimise wind farms with graph transformers

Matthew Piggott Information

University

Position

Professor Earth Science and Engineering

Citations(all)

6476

Citations(since 2020)

3306

Cited By

4435

hIndex(all)

42

hIndex(since 2020)

28

i10Index(all)

124

i10Index(since 2020)

81

Email

University Profile Page

Imperial College London

Google Scholar

View Google Scholar Profile

Matthew Piggott Skills & Research Interests

Computational Science

Data Science

Computational Fluid Dynamics

Offshore Renewable Energy

Coastal Hazards

Top articles of Matthew Piggott

Title

Journal

Author(s)

Publication Date

An unsupervised learning approach for predicting wind farm power and downstream wakes using weather patterns

Journal of Advances in Modeling Earth Systems

Mariana CA Clare

Simon C Warder

Robert Neal

B Bhaskaran

Matthew D Piggott

2024/2

Latent Neural Mapping for Hydrological Data Assimilation in Flood Prediction

Kun Wang

Sibo Cheng

Matthew Piggott

Sarah L Dance

Rossella Arcucci

2024/3/7

Tidal turbine array modelling using goal-oriented mesh adaptation

Journal of Ocean Engineering and Marine Energy

Joseph G Wallwork

Athanasios Angeloudis

Nicolas Barral

Lucas Mackie

Stephan C Kramer

...

2024/2

Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series

Myriam Prasow-Émond

Yves Plancherel

Philippa J Mason

Matthew D Piggott

Jonas Wahl

2024/3/7

Measuring Marine Hydrodynamics from Space Using Planet Satellite Imagery

James Tlhomole

Matthew Piggott

Graham Hughes

2024/3/7

Applications of Data Assimilation and Parameter Calibration with Multi-Resolution Measurements of Seawater Temperature for Hydrodynamic Modeling of Shallow, Tidal Environments

Nada Alsulaiman

Maarten Van Reeuwijk

Matthew Piggott

2024/3/7

Nearshore tsunami amplitudes across the Maldives archipelago due to worst-case seismic scenarios in the Indian Ocean

Natural Hazards and Earth System Sciences Discussions

Shuaib Rasheed

Simon C Warder

Yves Plancherel

Matthew D Piggott

2022/3/18

Learning to optimise wind farms with graph transformers

Applied Energy

Siyi Li

Arnaud Robert

A Aldo Faisal

Matthew D Piggott

2024/4/1

Towards a fully unstructured ocean model for ice shelf cavity environments: Model development and verification using the Firedrake finite element framework

Ocean Modelling

William I Scott

Stephan C Kramer

Paul R Holland

Keith W Nicholls

Martin J Siegert

...

2023/4/1

Physical Modelling of Tidal Stream Turbine Wake Structures under Yaw Conditions

Energies

Can Zhang

Jisheng Zhang

Athanasios Angeloudis

Yudi Zhou

Stephan C Kramer

...

2023/2/9

Machine Learning Assisted Mesh Adaptation for Geophysical Fluid Dynamics

Siyi Li

Eleda Johnson

Joseph G Wallwork

Stephan C Kramer

Matthew D Piggott

2023

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

Renewable Energy

Sokratis J Anagnostopoulos

Jens Bauer

Mariana CA Clare

Matthew D Piggott

2023/12/1

A parameter-free LES model for anisotropic mesh adaptivity

Computer Methods in Applied Mechanics and Engineering

JE Avalos-Patiño

SJ Neethling

MD Piggott

2023/11/1

End-to-end wind turbine wake modelling with deep graph representation learning

Applied Energy

Siyi Li

Mingrui Zhang

Matthew D Piggott

2023/6/1

Multi-scale hydro-morphodynamic modelling using mesh movement methods

GEM-International Journal on Geomathematics

Mariana CA Clare

Joseph G Wallwork

Stephan C Kramer

Hilary Weller

Colin J Cotter

...

2022/12

Modelling landslide generated waves using the discontinuous finite element method

International Journal for Numerical Methods in Fluids

Wei Pan

Stephan C Kramer

Matthew D Piggott

Xiping Yu

2022

Combining shallow-water and analytical wake models for tidal-array micro-siting

Journal of Ocean Engineering and Marine Energy

Connor Jordan

Davor Dundovic

Anastasia K Fragkou

Georgios Deskos

Daniel S Coles

...

2022/3/9

Constraints on long-term cliff retreat and intertidal weathering at weak rock coasts using cosmogenic 10Be, nearshore topography and numerical modelling

Earth Surface Dynamics Discussions

Jennifer R Shadrick

Dylan H Rood

Martin D Hurst

Matthew D Piggott

Klaus M Wilcken

...

2022/6/7

Investigating microscale patchiness of motile microbes under turbulence in a simulated convective mixed layer

PLoS Computational Biology

Alexander Kier Christensen

Matthew D Piggott

Erik van Sebille

Maarten van Reeuwijk

Samraat Pawar

2022/7/27

Sea-level rise will likely accelerate rock coast cliff retreat rates

Nature Communications

Jennifer R Shadrick

Dylan H Rood

Martin D Hurst

Matthew D Piggott

Bethany G Hebditch

...

2022/11/18

See List of Professors in Matthew Piggott University(Imperial College London)