Rupert W. Nash

807 total citations
15 papers, 477 citations indexed

About

Rupert W. Nash is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition and Condensed Matter Physics. According to data from OpenAlex, Rupert W. Nash has authored 15 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computational Mechanics, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Condensed Matter Physics. Recurrent topics in Rupert W. Nash's work include Lattice Boltzmann Simulation Studies (10 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Blood properties and coagulation (3 papers). Rupert W. Nash is often cited by papers focused on Lattice Boltzmann Simulation Studies (10 papers), Generative Adversarial Networks and Image Synthesis (4 papers) and Blood properties and coagulation (3 papers). Rupert W. Nash collaborates with scholars based in United Kingdom, India and Germany. Rupert W. Nash's co-authors include Michael E. Cates, R. Adhikari, Peter V. Coveney, Miguel O. Bernabéu, James Hetherington, Derek Groen, Julien Tailleur, Timm Krüger, Davide Marenduzzo and Alexander Morozov and has published in prestigious journals such as Physical Review Letters, Biophysical Journal and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Rupert W. Nash

13 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rupert W. Nash United Kingdom	9	178	166	161	64	55	15	477
Gwennou Coupier France	17	99 0.6×	210 1.3×	339 2.1×	56 0.9×	26 0.5×	34	936
Zaiyi Shen France	12	123 0.7×	111 0.7×	142 0.9×	21 0.3×	19 0.3×	21	403
Имре Вaргa Hungary	13	35 0.2×	66 0.4×	48 0.3×	46 0.7×	17 0.3×	41	495
Alexander Farutin France	18	202 1.1×	247 1.5×	306 1.9×	87 1.4×	28 0.5×	41	862
Daiki Matsunaga Japan	14	251 1.4×	96 0.6×	251 1.6×	60 0.9×	24 0.4×	36	492
Ivan Cimrák Slovakia	13	36 0.2×	195 1.2×	148 0.9×	13 0.2×	18 0.3×	63	531
Salman Akhtar Pakistan	22	13 0.1×	518 3.1×	789 4.9×	25 0.4×	27 0.5×	50	1.0k
Raju Viswanathan United States	12	35 0.2×	25 0.2×	132 0.8×	24 0.4×	13 0.2×	29	859
S. Mikoshiba Japan	11	39 0.2×	24 0.1×	62 0.4×	36 0.6×	5 0.1×	53	461
Yuguang Yang United States	17	268 1.5×	5 0.0×	264 1.6×	50 0.8×	46 0.8×	43	695

Countries citing papers authored by Rupert W. Nash

Since Specialization

Citations

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

Fields of papers citing papers by Rupert W. Nash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rupert W. Nash

This figure shows the co-authorship network connecting the top 25 collaborators of Rupert W. Nash. A scholar is included among the top collaborators of Rupert W. Nash 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 Rupert W. Nash. Rupert W. Nash is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Brown, Nick, et al.. (2024). Predicting accurate batch queue wait times on production supercomputers by combining machine learning techniques. Concurrency and Computation Practice and Experience. 36(15).

Bernabéu, Miguel O., Martin L. Jones, Rupert W. Nash, et al.. (2018). PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling. Biophysical Journal. 114(9). 2052–2058. 18 indexed citations

Richardson, Robin A., et al.. (2018). Modeling Patient-Specific Magnetic Drug Targeting Within the Intracranial Vasculature. Frontiers in Physiology. 9. 331–331. 25 indexed citations

Stenhammar, Joakim, Cesare Nardini, Rupert W. Nash, Davide Marenduzzo, & Alexander Morozov. (2017). Role of Correlations in the Collective Behavior of Microswimmer Suspensions. Physical Review Letters. 119(2). 28005–28005. 61 indexed citations

Henrich, Oliver, Timm Krüger, Rupert W. Nash, Dhiraj V. Patil, & Kevin Stratford. (2016). The 24th International Conference on Discrete Simulation of Fluid Dynamics in Edinburgh, Scotland. Journal of Computational Science. 17. 307–308.

Puurtinen, Tuomas, J. Toivanen, Keijo Mattila, et al.. (2016). Coupling of lattice-Boltzmann solvers with suspended particles using the MPI intercommunication framework. Advances in Engineering Software. 111. 52–57. 1 indexed citations

Nash, Rupert W., Miguel O. Bernabéu, James Hetherington, et al.. (2014). Choice of boundary condition for lattice-Boltzmann simulation of moderate-Reynolds-number flow in complex domains. Physical Review E. 89(2). 23303–23303. 47 indexed citations

Bernabéu, Miguel O., Martin L. Jones, Jens Hedegaard Nielsen, et al.. (2014). Computer simulations reveal complex distribution of haemodynamic forces in a mouse retina model of angiogenesis. Journal of The Royal Society Interface. 11(99). 20140543–20140543. 76 indexed citations

Bernabéu, Miguel O., Rupert W. Nash, Derek Groen, et al.. (2013). Impact of blood rheology on wall shear stress in a model of the middle cerebral artery. Interface Focus. 3(2). 20120094–20120094. 44 indexed citations

10.

Groen, Derek, et al.. (2013). Analysing and Modelling the Performance of the HemeLB Lattice-Boltzmann Simulation Environment. UCL Discovery (University College London). 43 indexed citations

11.

Nash, Rupert W., Miguel O. Bernabéu, James Hetherington, et al.. (2012). Choice of boundary condition and collision operator for lattice-Boltzmann simulation of moderate Reynolds number flow in complex domains. arXiv (Cornell University). 2 indexed citations

12.

Basermann, Achim, et al.. (2012). Enabling In Situ Pre- and Post-processing for Exascale Hemodynamic Simulations - A Co-design Study with the Sparse Geometry Lattice-Boltzmann Code HemeLB. elib (German Aerospace Center). 662–668. 5 indexed citations

13.

Nash, Rupert W., R. Adhikari, Julien Tailleur, & Michael E. Cates. (2010). Run-and-Tumble Particles with Hydrodynamics: Sedimentation, Trapping, and Upstream Swimming. Physical Review Letters. 104(25). 258101–258101. 105 indexed citations

14.

Nash, Rupert W., R. Adhikari, & Michael E. Cates. (2008). Singular forces and pointlike colloids in lattice Boltzmann hydrodynamics. Physical Review E. 77(2). 26709–26709. 43 indexed citations

15.

Massen, Claire P., Jonathan P. K. Doye, & Rupert W. Nash. (2007). Exploring the origins of the power-law properties of energy landscapes: An egg-box model. Physica A Statistical Mechanics and its Applications. 382(2). 683–692. 7 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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