Geoffrey Bomarito

679 total citations
28 papers, 398 citations indexed

About

Geoffrey Bomarito is a scholar working on Mechanical Engineering, Mechanics of Materials and Statistics, Probability and Uncertainty. According to data from OpenAlex, Geoffrey Bomarito has authored 28 papers receiving a total of 398 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Mechanical Engineering, 7 papers in Mechanics of Materials and 7 papers in Statistics, Probability and Uncertainty. Recurrent topics in Geoffrey Bomarito's work include Probabilistic and Robust Engineering Design (7 papers), Metal Forming Simulation Techniques (5 papers) and Optical measurement and interference techniques (5 papers). Geoffrey Bomarito is often cited by papers focused on Probabilistic and Robust Engineering Design (7 papers), Metal Forming Simulation Techniques (5 papers) and Optical measurement and interference techniques (5 papers). Geoffrey Bomarito collaborates with scholars based in United States, United Kingdom and Austria. Geoffrey Bomarito's co-authors include Jacob Hochhalter, Timothy Ruggles, Andrew Cannon, James E. Warner, Patrick E. Leser, William P. Leser, D.H. Warner, John M Emery, John A. Newman and Richard Qiu and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Journal of the Mechanics and Physics of Solids.

In The Last Decade

Geoffrey Bomarito

25 papers receiving 389 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Geoffrey Bomarito United States 11 155 121 103 63 55 28 398
Eryi Hu China 13 231 1.5× 185 1.5× 76 0.7× 50 0.8× 23 0.4× 37 457
Ruijin Cang United States 5 137 0.9× 53 0.4× 101 1.0× 134 2.1× 133 2.4× 7 448
Florian Bugarin France 10 136 0.9× 205 1.7× 51 0.5× 82 1.3× 20 0.4× 30 425
Éric Florentin France 12 95 0.6× 126 1.0× 184 1.8× 166 2.6× 16 0.3× 33 407
Houpu Yao United States 10 134 0.9× 38 0.3× 102 1.0× 177 2.8× 86 1.6× 21 560
Yuxi Xie United States 10 88 0.6× 22 0.2× 90 0.9× 92 1.5× 82 1.5× 31 465
Fan Hong Singapore 8 194 1.3× 54 0.4× 86 0.8× 98 1.6× 14 0.3× 49 458
Jianzhong Hu China 13 187 1.2× 30 0.2× 74 0.7× 50 0.8× 39 0.7× 40 488
Huanlin Liu China 13 115 0.7× 93 0.8× 135 1.3× 308 4.9× 11 0.2× 81 699

Countries citing papers authored by Geoffrey Bomarito

Since Specialization
Citations

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

Fields of papers citing papers by Geoffrey Bomarito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geoffrey Bomarito

This figure shows the co-authorship network connecting the top 25 collaborators of Geoffrey Bomarito. A scholar is included among the top collaborators of Geoffrey Bomarito 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 Geoffrey Bomarito. Geoffrey Bomarito 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.
Bomarito, Geoffrey, et al.. (2025). Call for Action: towards the next generation of symbolic regression benchmark. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2529–2538.
2.
Warner, James E., et al.. (2024). Covariance Expressions for Multifidelity Sampling with Multioutput, Multistatistic Estimators: Application to Approximate Control Variates. SIAM/ASA Journal on Uncertainty Quantification. 12(3). 1005–1049. 5 indexed citations
3.
Emery, John M, et al.. (2023). Generalizing the Gurson model using symbolic regression and transfer learning to relax inherent assumptions. Modelling and Simulation in Materials Science and Engineering. 31(8). 85005–85005. 7 indexed citations
4.
Bomarito, Geoffrey, et al.. (2023). Inherently interpretable machine learning solutions to differential equations. Engineering With Computers. 40(4). 2349–2361. 2 indexed citations
5.
Bomarito, Geoffrey, et al.. (2022). Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 526–529. 10 indexed citations
6.
Gramacy, Robert B., et al.. (2022). Entropy-based adaptive design for contour finding and estimating reliability. Journal of Quality Technology. 55(1). 43–60. 6 indexed citations
7.
Bomarito, Geoffrey, et al.. (2021). Development of interpretable, data-driven plasticity models with symbolic regression. Computers & Structures. 252. 106557–106557. 50 indexed citations
8.
Warner, James E., et al.. (2021). Multi-Model Monte Carlo Estimators for Trajectory Simulation. AIAA Scitech 2021 Forum. 4 indexed citations
9.
Warner, James E., Geoffrey Bomarito, Jacob Hochhalter, et al.. (2020). A Computationally-Efficient Probabilistic Approach to Model-Based Damage Diagnosis. International Journal of Prognostics and Health Management. 8(2). 26–26. 6 indexed citations
10.
Leser, Patrick E., James E. Warner, William P. Leser, et al.. (2020). A digital twin feasibility study (Part II): Non-deterministic predictions of fatigue life using in-situ diagnostics and prognostics. Engineering Fracture Mechanics. 229. 106903–106903. 56 indexed citations
11.
Leser, Patrick E., Jacob Hochhalter, James E. Warner, et al.. (2018). Sequential Monte Carlo: Enabling Real-time and High-fidelity Prognostics. Annual Conference of the PHM Society. 10(1). 4 indexed citations
12.
Ruggles, Timothy, Geoffrey Bomarito, Richard Qiu, & Jacob Hochhalter. (2018). New levels of high angular resolution EBSD performance via inverse compositional Gauss–Newton based digital image correlation. Ultramicroscopy. 195. 85–92. 26 indexed citations
13.
Ruggles, Timothy, Geoffrey Bomarito, Andrew Cannon, & Jacob Hochhalter. (2017). Selectively Electron-Transparent Microstamping Toward Concurrent Digital Image Correlation and High-Angular Resolution Electron Backscatter Diffraction (EBSD) Analysis. Microscopy and Microanalysis. 23(6). 1091–1095. 10 indexed citations
14.
Bomarito, Geoffrey & D.H. Warner. (2017). Predicting the ductile failure of Al5083-H116 specimens with a mechanistic model and no free fitting parameters. International Journal of Solids and Structures. 112. 25–34. 3 indexed citations
15.
Bomarito, Geoffrey, Jacob Hochhalter, & Timothy Ruggles. (2017). Development of Optimal Multiscale Patterns for Digital Image Correlation via Local Grayscale Variation. Experimental Mechanics. 58(7). 1169–1180. 23 indexed citations
16.
Bomarito, Geoffrey, et al.. (2016). Plasticity Tool for Predicting Shear Nonlinearity of Unidirectional Laminates Under Multiaxial Loading. 2 indexed citations
17.
Bomarito, Geoffrey, Jacob Hochhalter, & Andrew Cannon. (2016). Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements. NASA Technical Reports Server (NASA). 1 indexed citations
18.
Cannon, Andrew, et al.. (2015). MicroStamping for Improved Speckle Patterns to Enable Digital Image Correlation. Microscopy and Microanalysis. 21(S3). 451–452. 20 indexed citations
19.
Bomarito, Geoffrey, Yan Lin, & D.H. Warner. (2015). An atomistic modeling survey of the shear strength of twist grain boundaries in aluminum. Scripta Materialia. 101. 72–75. 9 indexed citations
20.
Bomarito, Geoffrey & D.H. Warner. (2014). Micromechanical investigation of ductile failure in Al 5083-H116 via 3D unit cell modeling. Journal of the Mechanics and Physics of Solids. 74. 97–110. 18 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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