Philip Avery

1.9k citations
50 papers · 1.3k indexed · 1 hit paper · h-index 21

Philip Avery

49 papers receiving 1.2k citations

Hit Papers

A mechanics‐informed artificial neural network approach i...12920222026202320244080120

Peers

Philip Avery
Comparison fields: 5 of 61
  • Statistics, Probability and Uncertainty 364
  • Statistical and Nonlinear Physics 579
  • Computational Mechanics 420
  • Numerical Analysis 77
  • Mechanics of Materials 314
Replace Boris Krämer with:
Boris Krämer United States
Ludovic Chamoin France
David Ryckelynck France
Alexander P. Seyranian Russia
W. Gawroński United States
Fai Ma United States
Ben Blackwell United States
Julien Cortial France
K. Huseyin Canada
Fehmi Cirak United Kingdom
Philip Avery relative to Boris Krämer United States Boris Krämer's profile →
Citations per field
00.5×1.7×
Boris Krämer · 1×
Citations per year

Countries citing papers authored by Philip Avery

Since Specialization
Citations

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

Fields of papers citing papers by Philip Avery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Philip Avery, 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 Philip Avery Line = papers co-authored together Philip Avery links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20241
3 20241
4 20227
5 202210
6 202210
7 202020
8 20191
9 201933
10 20195
11 20185
12 201821
13 20189
14 201739
15 201521
16 200932
17 200931
18
A method to solve spectral stochastic nite element problems for large-scale systems
20081
19 200613
20 200030

About Philip Avery

Philip Avery is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Applied Mathematics, having authored 50 papers that have together received 1.3k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (12 papers), Aerospace Engineering and Energy Systems (10 papers), Gas Dynamics and Kinetic Theory (10 papers), Probabilistic and Robust Engineering Design (9 papers), Computational Fluid Dynamics and Aerodynamics (9 papers), Structural Load-Bearing Analysis (7 papers), Advanced Numerical Methods in Computational Mathematics (7 papers) and Structural Health Monitoring Techniques (7 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (364 citations), Statistical and Nonlinear Physics (579 citations) and Computational Mechanics (420 citations). Philip Avery has collaborated with scholars based in United States, Australia and France. Frequent co-authors include Charbel Farhat, Todd Chapman, Julien Cortial, Radek Tezaur, Jason Rabinovitch, Jing Li, John H. Lau, Mahen Mahendran, Matthew J. Zahr and Jing Li. Their work appears in journals such as International Journal for Numerical Methods in Engineering, Computer Methods in Applied Mechanics and Engineering, AIAA Journal, Journal of Structural Engineering and Advances in Structural 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026