Matt Goodro

504 citations
16 papers · 431 · h-index 10

Impact in

Papers in

    • Turbomachinery Performance and Optimization 7
    • Aerodynamics and Acoustics in Jet Flows 7
    • Aerodynamics and Fluid Dynamics Research 3
    • Fluid Dynamics and Turbulent Flows 12
    • Combustion and flame dynamics 1

Matt Goodro

16 papers receiving 411 citations

Peers

Matt Goodro
Comparison fields: 5 of 43
  • Computational Mechanics 321
  • Mechanical Engineering 339
  • Aerospace Engineering 207
  • Cognitive Neuroscience 34
  • Radiology, Nuclear Medicine and Imaging 25
Replace Svenja Ettl with:
Svenja Ettl Germany
Junchong Yu China
Nigel H. S. Smith United Kingdom
Yongming Guo China
Luke R. Jackson United States
Steven J. Olson United States
Michael J. Doty United States
Dong Jun Huang China
A. Margrethe Lindemann United States
Chao-Cheng Shiau United States
Matt Goodro relative to Svenja Ettl Germany Svenja Ettl's profile →
Citations per field
00.5×5×10×15.9×
Svenja Ettl · 1×
Citations per year

Countries citing papers authored by Matt Goodro

Since Specialization
Citations

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

Fields of papers citing papers by Matt Goodro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Matt Goodro, 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 Matt Goodro Line = papers co-authored together Matt Goodro links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 200671
2 200869
3 201266
4 200648
5 201242
6 200829
7 201028
8 201323
9 200521
10 201414
11 20057
12 20076
13 20113
14 20062
15 20121
16 20071

About Matt Goodro

Matt Goodro is a scholar working on Aerospace Engineering, Computational Mechanics, Mechanical Engineering, Neurology and Ocean Engineering, having authored 16 papers that have together received 431 indexed citations. Recurring topics across this work include Heat Transfer Mechanisms (14 papers), Fluid Dynamics and Turbulent Flows (12 papers), Turbomachinery Performance and Optimization (7 papers), Aerodynamics and Acoustics in Jet Flows (7 papers), Aerodynamics and Fluid Dynamics Research (3 papers), Particle Dynamics in Fluid Flows (1 paper), Optical Imaging and Spectroscopy Techniques (1 paper) and Combustion and flame dynamics (1 paper). The work is most often cited by research in Computational Mechanics (321 citations), Mechanical Engineering (339 citations), Aerospace Engineering (207 citations), Cognitive Neuroscience (34 citations) and Radiology, Nuclear Medicine and Imaging (25 citations). Matt Goodro has collaborated with scholars based in United Kingdom, United States and South Korea. Frequent co-authors include Phil Ligrani, Hee-Koo Moon, Mike Fox, Jongmyung Park, George Fein, Brian Patenaude, Phillip M. Ligrani, Michael D. Fox, Q. Q. Zhang and Qiang Zhang. Their work appears in journals such as ASME Journal of Heat and Mass Transfer, International Journal of Heat and Mass Transfer, Journal of Turbomachinery, Psychiatry Research Neuroimaging and Journal of Thermophysics and Heat Transfer.

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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