John M Emery

826 total citations
28 papers, 406 citations indexed

About

John M Emery is a scholar working on Mechanics of Materials, Mechanical Engineering and Materials Chemistry. According to data from OpenAlex, John M Emery has authored 28 papers receiving a total of 406 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Mechanics of Materials, 12 papers in Mechanical Engineering and 10 papers in Materials Chemistry. Recurrent topics in John M Emery's work include Microstructure and mechanical properties (6 papers), Probabilistic and Robust Engineering Design (5 papers) and Fatigue and fracture mechanics (5 papers). John M Emery is often cited by papers focused on Microstructure and mechanical properties (6 papers), Probabilistic and Robust Engineering Design (5 papers) and Fatigue and fracture mechanics (5 papers). John M Emery collaborates with scholars based in United States, United Kingdom and Canada. John M Emery's co-authors include Richard Field, Jacob Hochhalter, Mary H. McGrath, Joseph E. Bishop, Jamshid Ghajar, Geoffrey Bomarito, David John Littlewood, Philip S. Barie, Brad Boyce and Luke N. Brewer and has published in prestigious journals such as Acta Materialia, Journal of neurosurgery and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

John M Emery

26 papers receiving 393 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John M Emery United States	13	139	121	89	70	64	28	406
Kirubel Teferra United States	12	121 0.9×	79 0.7×	66 0.7×	69 1.0×	116 1.8×	24	384
Qiang Lei China	10	209 1.5×	208 1.7×	29 0.3×	72 1.0×	119 1.9×	28	624
Fengjiao Guan China	15	86 0.6×	41 0.3×	20 0.2×	298 4.3×	140 2.2×	42	537
Wing K. Liu United States	13	216 1.6×	466 3.9×	96 1.1×	194 2.8×	46 0.7×	47	851
Jeong Ho Kim South Korea	13	144 1.0×	115 1.0×	25 0.3×	43 0.6×	20 0.3×	50	503
Emil Manoach Bulgaria	14	196 1.4×	482 4.0×	67 0.8×	479 6.8×	28 0.4×	59	929
Ali Abdul‐Aziz United States	10	151 1.1×	125 1.0×	57 0.6×	126 1.8×	12 0.2×	71	496
Gioacchino Alotta Italy	18	55 0.4×	291 2.4×	178 2.0×	231 3.3×	70 1.1×	43	809
M Puso United States	10	64 0.5×	456 3.8×	42 0.5×	112 1.6×	14 0.2×	15	723
B. M. Kwak South Korea	13	88 0.6×	116 1.0×	7 0.1×	97 1.4×	124 1.9×	30	622

Countries citing papers authored by John M Emery

Since Specialization

Citations

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

Fields of papers citing papers by John M Emery

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John M Emery

This figure shows the co-authorship network connecting the top 25 collaborators of John M Emery. A scholar is included among the top collaborators of John M Emery 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 John M Emery. John M Emery 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

Emery, John M, et al.. (2025). Learning implicit yield surface models with uncertainty quantification for noisy datasets. Computer Methods in Applied Mechanics and Engineering. 436. 117738–117738.

Emery, John M, et al.. (2024). Stress intensity factor models using mechanics-guided decomposition and symbolic regression. Engineering Fracture Mechanics. 310. 110432–110432. 8 indexed citations

Lester, Brian, et al.. (2023). Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression. Journal of the Mechanics and Physics of Solids. 181. 105472–105472. 8 indexed citations

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

Johnson, Kyle, et al.. (2022). Failure classification of porous additively manufactured parts using Deep Learning. Computational Materials Science. 204. 111098–111098. 11 indexed citations

Bomarito, Geoffrey, et al.. (2021). Development of interpretable, data-driven plasticity models with symbolic regression. Computers & Structures. 252. 106557–106557. 50 indexed citations

Emery, John M, et al.. (2019). Cohesive Zone Models for Reduced-Order Fastener Failure. AIAA Scitech 2019 Forum. 1 indexed citations

Lim, Hojun, et al.. (2019). Relating Microstructure to Defect Behavior in AA6061 Using a Combined Computational and Multiscale Electron Microscopy Approach. SSRN Electronic Journal. 1 indexed citations

Lim, Hojun, et al.. (2019). Relating microstructure to defect behavior in AA6061 using a combined computational and multiscale electron microscopy approach. Acta Materialia. 174. 81–91. 15 indexed citations

10.

Emery, John M, Mircea Grigoriu, & Richard Field. (2016). Bayesian methods for characterizing unknown parameters of material models. Applied Mathematical Modelling. 40(13-14). 6395–6411. 13 indexed citations

11.

Bishop, Joseph E., John M Emery, Richard Field, Christopher R. Weinberger, & David John Littlewood. (2015). Direct numerical simulations in solid mechanics for understanding the macroscale effects of microscale material variability. Computer Methods in Applied Mechanics and Engineering. 287. 262–289. 35 indexed citations

12.

Emery, John M, et al.. (2015). Predicting laser weld reliability with stochastic reduced‐order models. International Journal for Numerical Methods in Engineering. 103(12). 914–936. 18 indexed citations

13.

Reedy, E.D. & John M Emery. (2014). A simple cohesive zone model that generates a mode-mixity dependent toughness. International Journal of Solids and Structures. 51(21-22). 3727–3734. 2 indexed citations

14.

Carroll, Jay, Luke N. Brewer, C.C. Battaile, Brad Boyce, & John M Emery. (2012). The effect of grain size on local deformation near a void-like stress concentration. International Journal of Plasticity. 39. 46–60. 32 indexed citations

15.

Battaile, Corbett Chandler., Luke N. Brewer, Brad Boyce, & John M Emery. (2010). Quantifying Uncertainty in Materials Properties from Microstructure Variability. APS. 2010. 1 indexed citations

16.

Emery, John M, Jacob Hochhalter, Paul A. Wawrzynek, Gerd Heber, & A.R. Ingraffea. (2009). DDSim: A hierarchical, probabilistic, multiscale damage and durability simulation system – Part I: Methodology and Level I. Engineering Fracture Mechanics. 76(10). 1500–1530. 14 indexed citations

17.

Miyazaki, Katsumasa, John M Emery, & Anthony R. Ingraffea. (2003). OS12W0406 Simplified method to calculate stress intensity factors for a surface crack in a weld of a pipe penetrating a thick plate with a stub tube. 2003.2(0). _OS12W0406–_OS12W0406. 1 indexed citations

18.

Emery, John M. (1995). SPECIFYING END RESULTS. Civil engineering. 65(8). 60–61. 2 indexed citations

19.

Hariri, Robert, Scott Shepard, Douglas Cohen, et al.. (1993). Traumatic brain injury, hemorrhagic shock, and fluid resuscitation: effects on intracranial pressure and brain compliance. Journal of neurosurgery. 79(3). 421–427. 67 indexed citations

20.

Hariri, Robert, Jam Ghajar, Douglas Cohen, et al.. (1989). Intracranial hypertension following traumatic brain injury associated with shock and resuscitation. 40. 483–485. 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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