Matthew W. Farthing

3.3k total citations
76 papers, 1.7k citations indexed

About

Matthew W. Farthing is a scholar working on Environmental Engineering, Computational Mechanics and Oceanography. According to data from OpenAlex, Matthew W. Farthing has authored 76 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Environmental Engineering, 28 papers in Computational Mechanics and 13 papers in Oceanography. Recurrent topics in Matthew W. Farthing's work include Groundwater flow and contamination studies (22 papers), Advanced Numerical Methods in Computational Mathematics (21 papers) and Computational Fluid Dynamics and Aerodynamics (10 papers). Matthew W. Farthing is often cited by papers focused on Groundwater flow and contamination studies (22 papers), Advanced Numerical Methods in Computational Mathematics (21 papers) and Computational Fluid Dynamics and Aerodynamics (10 papers). Matthew W. Farthing collaborates with scholars based in United States, United Kingdom and Italy. Matthew W. Farthing's co-authors include Christopher E. Kees, Cass T. Miller, Fred L. Ogden, Yuri Bazilevs, I. Akkerman, Paul T. Imhoff, Clint Dawson, Kathleen Fowler, C. T. Kelley and David J. Benson and has published in prestigious journals such as Scientific Reports, Water Resources Research and Journal of Computational Physics.

In The Last Decade

Matthew W. Farthing

68 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew W. Farthing United States	23	652	591	427	241	232	76	1.7k
Anis Younès France	28	685 1.1×	1.2k 2.1×	631 1.5×	315 1.3×	161 0.7×	120	2.4k
Marwan Fahs France	21	286 0.4×	908 1.5×	380 0.9×	293 1.2×	109 0.5×	101	1.5k
Christopher E. Kees United States	19	730 1.1×	266 0.5×	217 0.5×	135 0.6×	62 0.3×	64	1.2k
Charles Tong United States	21	206 0.3×	325 0.5×	163 0.4×	115 0.5×	228 1.0×	37	1.3k
C. L. Winter United States	24	189 0.3×	1.1k 1.9×	551 1.3×	373 1.5×	143 0.6×	64	1.7k
Abdolmajid Mohammadian Canada	26	540 0.8×	439 0.7×	672 1.6×	137 0.6×	659 2.8×	192	2.8k
Christopher Zoppou Australia	14	313 0.5×	534 0.9×	415 1.0×	237 1.0×	273 1.2×	34	1.3k
Wenqing Wang Germany	28	195 0.3×	954 1.6×	568 1.3×	350 1.5×	269 1.2×	139	2.5k
Bernd Flemisch Germany	22	701 1.1×	749 1.3×	251 0.6×	353 1.5×	29 0.1×	75	1.8k
Ivan Lunati Switzerland	23	866 1.3×	616 1.0×	236 0.6×	619 2.6×	75 0.3×	76	1.8k

Countries citing papers authored by Matthew W. Farthing

Since Specialization

Citations

This map shows the geographic impact of Matthew W. Farthing'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 W. Farthing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew W. Farthing more than expected).

Fields of papers citing papers by Matthew W. Farthing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew W. Farthing. 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 W. Farthing. The network helps show where Matthew W. Farthing may publish in the future.

Co-authorship network of co-authors of Matthew W. Farthing

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew W. Farthing. A scholar is included among the top collaborators of Matthew W. Farthing 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 W. Farthing. Matthew W. Farthing 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

Cohn, Nicholas, et al.. (2025). Examination of analytical shear stress predictions for coastal dune evolution. Earth Surface Dynamics. 13(1). 1–22. 1 indexed citations

Trahan, Corey J., et al.. (2024). Strongly Coupled 2D and 3D Shallow Water Models: Theory and Verification. Journal of Hydraulic Engineering. 151(1). 1 indexed citations

Hesser, Tyler, et al.. (2023). SCALABLE REAL-TIME DATA ASSIMILATION WITH VARIOUS DATA TYPES FOR ACCURATE SPATIOTEMPORAL NEARSHORE BATHYMETRY ESTIMATION. Coastal Engineering Proceedings. 156–156. 1 indexed citations

Farthing, Matthew W., et al.. (2023). Thermal modeling for autonomous vehicle simulations. 12–12.

Collins, Adam, et al.. (2023). Super-resolution and uncertainty estimation from sparse sensors of dynamical physical systems. Frontiers in Water. 5. 4 indexed citations

Farthing, Matthew W., et al.. (2022). Reduced Order Modeling Using Advection-Aware Autoencoders. Mathematical and Computational Applications. 27(3). 34–34. 11 indexed citations

Farthing, Matthew W., et al.. (2021). pyNIROM—A suite of python modules for non-intrusive reduced order modeling of time-dependent problems. Software Impacts. 10. 100129–100129. 2 indexed citations

Rowland, Michael A., Todd M. Swannack, Michael L. Mayo, et al.. (2021). COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications. Scientific Reports. 11(1). 10875–10875. 4 indexed citations

Collins, Adam, Katherine Brodie, A. Spicer Bak, Tyler Hesser, & Matthew W. Farthing. (2020). Nearshore Bathymetric Inversion and Uncertainty Estimation from Synthetic Imagery using a 2D Fully Convolutional Neural Network. AGU Fall Meeting Abstracts. 2020. 1 indexed citations

10.

Collins, Adam, Katherine Brodie, A. Spicer Bak, et al.. (2020). A 2D Fully Convolutional Neural Network for Nearshore And Surf-Zone Bathymetry Inversion from Synthetic Imagery of Surf-Zone using the Model Celeris.. National Conference on Artificial Intelligence. 2 indexed citations

11.

Lee, Jonghyun, et al.. (2019). Novel Data Assimilation Algorithm for Nearshore Bathymetry. Journal of Atmospheric and Oceanic Technology. 36(4). 699–715. 11 indexed citations

12.

Farthing, Matthew W., et al.. (2018). Modeling Nondilute Species Transport Using the Thermodynamically Constrained Averaging Theory. Water Resources Research. 54(9). 6656–6682. 9 indexed citations

13.

Farthing, Matthew W., et al.. (2016). POD-based model reduction for stabilized finite element approximations of shallow water flows. Journal of Computational and Applied Mathematics. 302. 50–70. 17 indexed citations

14.

Howington, Stacy E., et al.. (2010). A Generic Reaction-Based BioGeoChemical Simulator (RBBGCS), Version 1.0. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 1 indexed citations

15.

Pedit, Joseph A., et al.. (2010). Dense, viscous brine behavior in heterogeneous porous medium systems. Journal of Contaminant Hydrology. 115(1-4). 46–63. 5 indexed citations

16.

Kees, Christopher E., Matthew W. Farthing, Steven Mattis, & Clint Dawson. (2009). HOMOGENIZATION AND UPSCALING OF FLOW THROUGH VEGETATION. AGU Fall Meeting Abstracts. 2009.

17.

Kees, Christopher E., et al.. (2009). A Review of Methods for Moving Boundary Problems. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core). 4 indexed citations

18.

Farthing, Matthew W. & Christopher E. Kees. (2008). Implementation of Discontinuous Galerkin Methods for the Level Set Equation on Unstructured Meshes. US Army Corps of Engineers: Engineer Research and Development Center (Knowledge Core).

19.

Gasda, Sarah E., et al.. (2008). The influence of heterogeneity and spill conditions on NAPL dissolution fingering. AGU Fall Meeting Abstracts. 2008. 1 indexed citations

20.

Kees, Christopher E., et al.. (2002). Choices of scale and process complexity in hillslope models. AGUFM. 2002. 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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