Randal J. Barnes

1.1k total citations
36 papers, 665 citations indexed

About

Randal J. Barnes is a scholar working on Environmental Engineering, Artificial Intelligence and Civil and Structural Engineering. According to data from OpenAlex, Randal J. Barnes has authored 36 papers receiving a total of 665 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Environmental Engineering, 10 papers in Artificial Intelligence and 9 papers in Civil and Structural Engineering. Recurrent topics in Randal J. Barnes's work include Groundwater flow and contamination studies (8 papers), Geophysical and Geoelectrical Methods (5 papers) and Soil Geostatistics and Mapping (4 papers). Randal J. Barnes is often cited by papers focused on Groundwater flow and contamination studies (8 papers), Geophysical and Geoelectrical Methods (5 papers) and Soil Geostatistics and Mapping (4 papers). Randal J. Barnes collaborates with scholars based in United States, South Africa and Canada. Randal J. Barnes's co-authors include I. Janković, Melinda L. Erickson, Elizabeth A. Barnes, Otto D. L. Strack, Kwang-Ho You, Gédéon Dagan, David R. Steward, Mark J Severson, Lev Khazanovich and James R. Craig and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Research and Journal of Climate.

In The Last Decade

Randal J. Barnes

35 papers receiving 623 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Randal J. Barnes United States 15 323 174 122 92 91 36 665
Chuen‐Fa Ni Taiwan 17 557 1.7× 213 1.2× 139 1.1× 144 1.6× 33 0.4× 63 836
R. E. Volker Australia 16 583 1.8× 213 1.2× 94 0.8× 116 1.3× 96 1.1× 34 958
Falk Heße Germany 15 404 1.3× 146 0.8× 52 0.4× 42 0.5× 61 0.7× 39 718
Chantal de Fouquet France 15 366 1.1× 48 0.3× 105 0.9× 63 0.7× 50 0.5× 54 654
Glenn Hammond United States 21 887 2.7× 194 1.1× 131 1.1× 161 1.8× 276 3.0× 75 1.4k
Liangming Liu China 17 298 0.9× 136 0.8× 154 1.3× 302 3.3× 45 0.5× 69 968
Lloyd R. Townley Australia 12 799 2.5× 206 1.2× 173 1.4× 247 2.7× 56 0.6× 21 1.1k
Steffen Mehl United States 22 943 2.9× 248 1.4× 120 1.0× 128 1.4× 64 0.7× 47 1.3k
Juan J. Hidalgo Spain 15 806 2.5× 157 0.9× 191 1.6× 222 2.4× 75 0.8× 39 1.0k
Matthew Tonkin United States 14 811 2.5× 160 0.9× 127 1.0× 154 1.7× 54 0.6× 32 1.1k

Countries citing papers authored by Randal J. Barnes

Since Specialization
Citations

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

Fields of papers citing papers by Randal J. Barnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Randal J. Barnes. 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 Randal J. Barnes. The network helps show where Randal J. Barnes may publish in the future.

Co-authorship network of co-authors of Randal J. Barnes

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

All Works

20 of 20 papers shown
1.
Barnes, Elizabeth A., Randal J. Barnes, Mark DeMaria, et al.. (2025). Predicting Tropical Cyclone Track Forecast Errors Using a Probabilistic Neural Network. ArXiv.org. 4(2).
2.
Barnes, Elizabeth A., Randal J. Barnes, & Mark DeMaria. (2023). Sinh-arcsinh-normal distributions to add uncertainty to neural network regression tasks: Applications to tropical cyclone intensity forecasts. SHILAP Revista de lepidopterología. 2. 3 indexed citations
3.
Barnes, Elizabeth A., et al.. (2022). This Looks Like That There: Interpretable Neural Networks for Image Tasks When Location Matters. 1(3). 8 indexed citations
4.
Barnes, Elizabeth A. & Randal J. Barnes. (2021). Controlled Abstention Neural Networks for Identifying Skillful Predictions for Classification Problems. Journal of Advances in Modeling Earth Systems. 13(12). 8 indexed citations
5.
Barnes, Elizabeth A. & Randal J. Barnes. (2021). Controlled Abstention Neural Networks for Identifying Skillful Predictions for Regression Problems. Journal of Advances in Modeling Earth Systems. 13(12). 13 indexed citations
6.
Khazanovich, Lev, et al.. (2020). Non-destructive ultrasonic evaluation of construction variability effect on concrete pavement performance. International Journal of Pavement Research and Technology. 14(3). 385–396. 3 indexed citations
7.
Barnes, Randal J.. (2017). Shallow Unconfined Flow on a Sloping Base Redux. Ground Water. 56(4). 610–617. 1 indexed citations
8.
Khazanovich, Lev, et al.. (2016). Portland Cement Concrete Pavement Thickness Variation Versus Observed Pavement Distress. University of Minnesota Digital Conservancy (University of Minnesota). 1 indexed citations
9.
Khazanovich, Lev, et al.. (2013). Concrete Pavement Thickness Variation Assessment with Cores and Nondestructive Testing Measurements. Transportation Research Record Journal of the Transportation Research Board. 2347(1). 61–68. 10 indexed citations
10.
Barnes, Randal J.. (2010). MnROAD Data Mining, Evaluation and Quantification – Phase I. University of Minnesota Digital Conservancy (University of Minnesota). 1 indexed citations
11.
Erickson, Melinda L. & Randal J. Barnes. (2006). Arsenic concentration variability in public water system wells in Minnesota, USA. Applied Geochemistry. 21(2). 305–317. 17 indexed citations
12.
Erickson, Melinda L. & Randal J. Barnes. (2005). Well characteristics influencing arsenic concentrations in ground water. Water Research. 39(16). 4029–4039. 31 indexed citations
13.
Craig, James R., I. Janković, & Randal J. Barnes. (2005). The Nested Superblock Approach for Regional‐Scale Analytic Element Models. Ground Water. 44(1). 76–80. 8 indexed citations
14.
Erickson, Melinda L. & Randal J. Barnes. (2005). Glacial Sediment Causing Regional‐Scale Elevated Arsenic in Drinking Water. Ground Water. 43(6). 796–805. 50 indexed citations
15.
Barnes, Randal J.. (1993). Geostatistics for subgrade characterization. University of Minnesota Digital Conservancy (University of Minnesota). 1 indexed citations
16.
Barnes, Randal J.. (1991). The variogram sill and the sample variance. Mathematical Geology. 23(4). 673–678. 67 indexed citations
17.
Severson, Mark J & Randal J. Barnes. (1991). Geology, Mineralization, and Geostatistics of the Minnamax/Babbitt Cu-Ni Deposit (Local Boy Area), Minnesota: Part II: Mineralization and Geostatistics. University of Minnesota Digital Conservancy (University of Minnesota). 8 indexed citations
18.
Barnes, Randal J.. (1988). Bounding the required sample size for geologic site characterization. Mathematical Geology. 20(5). 477–490. 19 indexed citations
19.
Barnes, Randal J.. (1986). COST OF RISK AND THE VALUE OF INFORMATION IN MINE PLANNING.. 459–469. 1 indexed citations
20.
Barnes, Randal J.. (1961). Influence of Speed on Elements of Draft of a Tillage Tool. Transactions of the ASAE. 4(1). 55–57. 28 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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