John Jakeman

57 papers receiving 1.2k citations

Peers

John Jakeman
Comparison fields: 5 of 109
  • Statistics, Probability and Uncertainty 695
  • Statistical and Nonlinear Physics 275
  • Computational Mathematics 10
  • Computational Theory and Mathematics 263
  • Environmental Engineering 198
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Paul G. Constantine United States
Bertrand Iooss France
Charles Tong United States
Géraud Blatman France
Daniel O’Malley United States
Xiaoliang Wan United States
Tiangang Cui Australia
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Countries citing papers authored by John Jakeman

Since Specialization
Citations

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

Fields of papers citing papers by John Jakeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Jakeman. 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 John Jakeman. The network helps show where John Jakeman may publish in the future.

Co-authors

The 25 scholars most cited alongside John Jakeman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Jakeman Line = papers co-authored together John Jakeman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019120
2 2015117
3 202079
4 202073
5 201069
6 201961
7 202055
8 201645
9 201743
10
ADAPTIVE LEJA SPARSE GRID CONSTRUCTIONS FOR STOCHASTIC COLLOCATION AND HIGH-DIMENSIONAL APPROXIMATION
201640
11 201339
12 202138
13 201135
14 202031
15 201930
16 201030
17 201530
18 201828
19
Developments in integrated environmental assessment
200724
20 201823

About John Jakeman

John Jakeman is a scholar working on Statistics, Probability and Uncertainty, Civil and Structural Engineering, Statistical and Nonlinear Physics, Computational Theory and Mathematics and Artificial Intelligence, having authored 58 papers that have together received 1.2k indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (40 papers), Advanced Multi-Objective Optimization Algorithms (13 papers), Structural Health Monitoring Techniques (12 papers), Model Reduction and Neural Networks (10 papers), Optimal Experimental Design Methods (6 papers), Structural Response to Dynamic Loads (4 papers), Groundwater flow and contamination studies (4 papers) and Gaussian Processes and Bayesian Inference (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (695 citations), Statistical and Nonlinear Physics (275 citations), Computational Mathematics (10 citations), Computational Theory and Mathematics (263 citations) and Environmental Engineering (198 citations). John Jakeman has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Michael Eldred, Akil Narayan, Dongbin Xiu, Alex Gorodetsky, Gianluca Geraci, Khachik Sargsyan, Timothy Wildey, Tong Qin, Barry Croke and Troy Butler. Their work appears in journals such as Journal of Computational Physics, SIAM Journal on Scientific Computing, Computer Methods in Applied Mechanics and Engineering, International Journal for Uncertainty Quantification and International Journal for Numerical Methods in Engineering.

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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