Julia Ling
Impact in
- Statistical and Nonlinear Physics top 0.5%
- Model Reduction and Neural Networks
- Computational Mechanics top 0.5%
- Fluid Dynamics and Turbulent Flows
- Computational Fluid Dynamics and Aerodynamics
- Combustion and flame dynamics
Papers in
-
- Model Reduction and Neural Networks 15
-
- Turbomachinery Performance and Optimization 22
- Co-authors
- Jeremy Alan Templeton (5 shared papers)Andrew J. Kurzawski (2 shared papers)John K. Eaton (23 shared papers)Reese Jones (1 shared paper)Erin Antono (10 shared papers)Bryce Meredig (7 shared papers)Christopher J. Elkins (9 shared papers)Julien Bodart (6 shared papers)
- Journals
- Journal of Turbomachinery (7 papers)International Journal of Heat and Fluid Flow (2 papers)Journal of Computational Physics (2 papers)Journal of Fluid Mechanics (2 papers)IEEE Transactions on Plasma Science (1 paper)
- Partner nations
- United StatesFranceAustralia
In The Last Decade
Julia Ling
60 papers receiving 3.4k citations
Julia Ling's Hit Papers
Peers
Comparison fields: 5 of 96
- Statistical and Nonlinear Physics 1.4k
- Computational Mechanics 1.2k
- Aerospace Engineering 608
- Materials Chemistry 553
- Geophysics 171
Countries citing papers authored by Julia Ling
This map shows the geographic impact of Julia Ling'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 Julia Ling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Ling more than expected).
Fields of papers citing papers by Julia Ling
This network shows the impact of papers produced by Julia Ling. 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 Julia Ling. The network helps show where Julia Ling may publish in the future.
Co-authors
The 25 scholars most cited alongside Julia Ling, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reynolds averaged turbulence modelling using deep neural networks with embedded invariance Hit paper breakdown → | 2016 | 1247 |
| 2 | Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty Hit paper breakdown → | 2015 | 330 |
| 3 | Machine learning strategies for systems with invariance properties Hit paper breakdown → | 2016 | 307 |
| 4 | 2018 | 199 | |
| 5 | 2009 | 181 | |
| 6 | 2017 | 151 | |
| 7 | 2017 | 77 | |
| 8 | 2017 | 65 | |
| 9 | 2017 | 61 | |
| 10 | 2013 | 59 | |
| 11 | 2015 | 58 | |
| 12 | 2020 | 56 | |
| 13 | 2016 | 44 | |
| 14 | 2020 | 41 | |
| 15 | 2018 | 36 | |
| 16 | 2020 | 33 | |
| 17 | 2010 | 32 | |
| 18 | 2012 | 28 | |
| 19 | 2016 | 27 | |
| 20 | 2017 | 27 |
About Julia Ling
Julia Ling is a scholar working on Statistical and Nonlinear Physics, Aerospace Engineering, Computational Mechanics, Materials Chemistry and Artificial Intelligence, having authored 60 papers that have together received 3.5k indexed citations. Recurring topics across this work include Turbomachinery Performance and Optimization (22 papers), Fluid Dynamics and Turbulent Flows (18 papers), Model Reduction and Neural Networks (15 papers), Computational Fluid Dynamics and Aerodynamics (13 papers), Machine Learning in Materials Science (12 papers), Plasma Diagnostics and Applications (2 papers), Neural Networks and Applications (2 papers) and Vacuum and Plasma Arcs (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (1.4k citations), Computational Mechanics (1.2k citations), Aerospace Engineering (608 citations), Materials Chemistry (553 citations) and Geophysics (171 citations). Julia Ling has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Jeremy Alan Templeton, Andrew J. Kurzawski, John K. Eaton, Reese Jones, Erin Antono, Bryce Meredig, Christopher J. Elkins, Julien Bodart, Maxwell Hutchinson and Minoru M. Freund. Their work appears in journals such as Journal of Turbomachinery, International Journal of Heat and Fluid Flow, Journal of Computational Physics, Journal of Fluid Mechanics and IEEE Transactions on Plasma Science.
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.