Matthew D. Piggott

6.6k total citations
173 papers, 3.9k citations indexed

About

Matthew D. Piggott is a scholar working on Computational Mechanics, Earth-Surface Processes and Atmospheric Science. According to data from OpenAlex, Matthew D. Piggott has authored 173 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computational Mechanics, 50 papers in Earth-Surface Processes and 49 papers in Atmospheric Science. Recurrent topics in Matthew D. Piggott's work include Wind Energy Research and Development (33 papers), Coastal and Marine Dynamics (27 papers) and Geological formations and processes (26 papers). Matthew D. Piggott is often cited by papers focused on Wind Energy Research and Development (33 papers), Coastal and Marine Dynamics (27 papers) and Geological formations and processes (26 papers). Matthew D. Piggott collaborates with scholars based in United Kingdom, United States and Norway. Matthew D. Piggott's co-authors include Christopher C. Pain, Gerard Gorman, Stephan C. Kramer, Peter A. Allison, A.J.H. Goddard, Alexandros Avdis, Athanasios Angeloudis, Simon W. Funke, Jon Hill and Patrick E. Farrell and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Remote Sensing of Environment.

In The Last Decade

Matthew D. Piggott

165 papers receiving 3.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Matthew D. Piggott United Kingdom	34	1.1k	1000	863	853	770	173	3.9k
Christopher C. Pain United Kingdom	48	1.2k 1.1×	3.5k 3.5×	1.0k 1.2×	538 0.6×	390 0.5×	329	8.6k
Gang Wang China	27	380 0.3×	539 0.5×	185 0.2×	700 0.8×	441 0.6×	256	2.7k
Kwok Fai Cheung United States	41	1.4k 1.3×	624 0.6×	223 0.3×	1.7k 2.0×	1.6k 2.1×	130	5.3k
Maurizio Brocchini Italy	35	1.2k 1.0×	1.2k 1.2×	164 0.2×	2.3k 2.7×	1.1k 1.4×	187	4.1k
Robert L. Street United States	45	1.7k 1.5×	4.2k 4.2×	949 1.1×	1.2k 1.4×	1.5k 1.9×	181	7.8k
Giuseppe Gambolati Italy	36	387 0.3×	814 0.8×	841 1.0×	312 0.4×	198 0.3×	189	4.4k
Pengzhi Lin China	40	1.2k 1.0×	3.6k 3.6×	560 0.6×	3.3k 3.9×	1.4k 1.8×	209	6.9k
Andrew W. Woods United Kingdom	49	2.3k 2.0×	1.4k 1.4×	735 0.9×	1.2k 1.4×	336 0.4×	266	8.6k
G. J. F. van Heijst Netherlands	40	1.2k 1.1×	2.3k 2.3×	803 0.9×	320 0.4×	1.1k 1.4×	182	5.6k
Hermann M. Fritz United States	41	1.6k 1.4×	653 0.7×	235 0.3×	1.5k 1.8×	641 0.8×	113	5.1k

Countries citing papers authored by Matthew D. Piggott

Since Specialization

Citations

This map shows the geographic impact of Matthew D. Piggott's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthew D. Piggott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew D. Piggott more than expected).

Fields of papers citing papers by Matthew D. Piggott

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew D. Piggott. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew D. Piggott. The network helps show where Matthew D. Piggott may publish in the future.

Co-authorship network of co-authors of Matthew D. Piggott

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew D. Piggott. A scholar is included among the top collaborators of Matthew D. Piggott based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew D. Piggott. Matthew D. Piggott is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Alosairi, Yousef, et al.. (2025). Measuring marine hydrodynamics from space using planet satellite imagery. Remote Sensing of Environment. 324. 114741–114741.

2.

Kramer, Stephan C., et al.. (2025). Anisotropic metric-based mesh adaptation for ice flow modelling in Firedrake. Geoscientific model development. 18(13). 4023–4044.

3.

Li, Siyi, et al.. (2025). Deep learning predicts real-world electric vehicle direct current charging profiles and durations. Nature Communications. 16(1). 10921–10921.

4.

Staffell, Iain, et al.. (2024). Improving wind power modelling through granular spatial and temporal bias correction of reanalysis data. Energy. 313. 133759–133759. 1 indexed citations

5.

Clare, Mariana, et al.. (2024). An Unsupervised Learning Approach for Predicting Wind Farm Power and Downstream Wakes Using Weather Patterns. Journal of Advances in Modeling Earth Systems. 16(2). 1 indexed citations

6.

Cheng, Xiaoming, et al.. (2024). Economics-constrained tidal turbine array layout optimisation at the Putuoshan–Hulu island waterway. Ocean Engineering. 314. 119618–119618. 1 indexed citations

7.

Zhang, Jisheng, et al.. (2023). Physical Modelling of Tidal Stream Turbine Wake Structures under Yaw Conditions. Energies. 16(4). 1742–1742. 4 indexed citations

8.

Angeloudis, Athanasios, et al.. (2023). Tidal turbine array modelling using goal-oriented mesh adaptation. Journal of Ocean Engineering and Marine Energy. 10(1). 193–216. 1 indexed citations

9.

Rood, Dylan H., et al.. (2023). Constraints on long-term cliff retreat and intertidal weathering at weak rock coasts using cosmogenic ¹⁰ Be, nearshore topography and numerical modelling. Earth Surface Dynamics. 11(3). 429–450. 3 indexed citations

10.

Zhang, Jisheng, et al.. (2022). Interactions between tidal stream turbine arrays and their hydrodynamic impact around Zhoushan Island, China. Ocean Engineering. 246. 110431–110431. 7 indexed citations

11.

Rood, Dylan H., et al.. (2022). Sea-level rise will likely accelerate rock coast cliff retreat rates. Nature Communications. 13(1). 7005–7005. 26 indexed citations

12.

Hurst, Martin D., et al.. (2021). Multi-objective optimisation of a rock coast evolution model with cosmogenic ¹⁰ Be analysis for the quantification of long-term cliff retreat rates. Earth Surface Dynamics. 9(6). 1505–1529. 7 indexed citations

13.

Coles, Daniel, Athanasios Angeloudis, Deborah Greaves, et al.. (2021). A review of the UK and British Channel Islands practical tidal stream energy resource. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 477(2255). 20210469–20210469. 67 indexed citations

14.

Ham, David A., et al.. (2021). Goal-Oriented Error Estimation and Mesh Adaptation for Tracer Transport Modelling. Computer-Aided Design. 145. 103187–103187. 2 indexed citations

15.

Hurst, Martin D., et al.. (2021). Multi-objective optimisation of a rock coast evolution model with cosmogenic ¹⁰ Be analysis for the quantification of long-term cliff retreat rates. 2 indexed citations

16.

Dargaville, Steven, et al.. (2021). Impact of inhomogeneous unsteady participating media in a coupled convection–radiation system using finite element based methods. International Journal of Heat and Mass Transfer. 176. 121452–121452. 2 indexed citations

17.

Kramer, Stephan C., et al.. (2020). Goal-oriented error estimation and mesh adaptation for shallow water modelling. SN Applied Sciences. 2(6). 9 indexed citations

18.

Piggott, Matthew D., et al.. (2018). Using Smoothed Particle Hydrodynamics to investigate the effect of complex slide rheology on landslide generated waves.. EGUGA. 8848. 1 indexed citations

19.

Viré, Axelle, Jiansheng Xiang, Matthew D. Piggott, Johannes Spinneken, & Christopher C. Pain. (2013). Numerical Modelling of Fluid-structure Interactions for Floating Wind Turbine Foundations. The Twenty-third International Offshore and Polar Engineering Conference. 1 indexed citations

20.

Wilson, C. R., G. S. Collins, & Matthew D. Piggott. (2009). Numerical modeling of landslide generated tsunami using adaptive unstructured meshes. EGU General Assembly Conference Abstracts. 2009. 916. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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