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
- Fluid Dynamics and Vibration Analysis
Papers in ⓘ
-
- Fluid Dynamics and Turbulent Flows 33
- Co-authors
- Jeremy Alan Templeton (5 shared papers)Andrew Kurzawski (2 shared papers)John K. Eaton (22 shared papers)Reese E. Jones (1 shared paper)Erin Antono (10 shared papers)Christopher J. Elkins (9 shared papers)Bryce Meredig (7 shared papers)Julien Bodart (6 shared papers)
- Journals
- Journal of Turbomachinery (7 papers)ACS Applied Materials & Interfaces (2 papers)International Journal of Heat and Fluid Flow (2 papers)Journal of Fluid Mechanics (2 papers)Journal of Computational Physics (2 papers)
- Partner nations
- United StatesFranceChina
In The Last Decade
Julia Ling
56 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Statistical and Nonlinear Physics 1.2k
- Computational Mechanics 1.7k
- Aerospace Engineering 911
- Statistics, Probability and Uncertainty 184
- Environmental Engineering 289
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 | 1068 |
| 2 | Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty Hit paper breakdown → | 2015 | 288 |
| 3 | Machine learning strategies for systems with invariance properties Hit paper breakdown → | 2016 | 263 |
| 4 | 2009 | 171 | |
| 5 | 2018 | 167 | |
| 6 | 2017 | 63 | |
| 7 | 2017 | 62 | |
| 8 | 2013 | 56 | |
| 9 | 2015 | 51 | |
| 10 | 2020 | 48 | |
| 11 | 2016 | 41 | |
| 12 | 2020 | 34 | |
| 13 | 2018 | 34 | |
| 14 | 2020 | 30 | |
| 15 | 2012 | 27 | |
| 16 | 2016 | 27 | |
| 17 | 2017 | 26 | |
| 18 | 2017 | 25 | |
| 19 | 2020 | 24 | |
| 20 | 2018 | 23 |
About Julia Ling
Julia Ling is a scholar working on Computational Mathematics, Computational Mechanics, Aerospace Engineering, Statistical and Nonlinear Physics and Mechanical Engineering, having authored 60 papers that have together received 2.9k indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (33 papers), Heat Transfer Mechanisms (21 papers), Turbomachinery Performance and Optimization (18 papers), Model Reduction and Neural Networks (12 papers), Machine Learning in Materials Science (11 papers), Nuclear Engineering Thermal-Hydraulics (4 papers), Probabilistic and Robust Engineering Design (4 papers) and X-ray Diffraction in Crystallography (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.2k citations), Computational Mechanics (1.7k citations), Aerospace Engineering (911 citations), Statistics, Probability and Uncertainty (184 citations) and Environmental Engineering (289 citations). Julia Ling has collaborated with scholars based in United States, France and China. Frequent co-authors include Jeremy Alan Templeton, Andrew Kurzawski, John K. Eaton, Reese E. Jones, Erin Antono, Christopher J. Elkins, Bryce Meredig, Julien Bodart, Maxwell Hutchinson and J. Tregloan-Reed. Their work appears in journals such as Journal of Turbomachinery, ACS Applied Materials & Interfaces, International Journal of Heat and Fluid Flow, Journal of Fluid Mechanics and Journal of Computational Physics.
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.