Julian Quick
Impact in
- Aerospace Engineering top 5%
- Wind Energy Research and Development
Papers in
-
- Wind Energy Research and Development 24
-
- Model Reduction and Neural Networks 4
- Co-authors
- Katherine Dykes (10 shared papers)Ryan King (7 shared papers)Pierre-Elouan Mikael Réthoré (12 shared papers)Andrew Ning (3 shared papers)Peter E. Hamlington (4 shared papers)Jennifer R. Annoni (1 shared paper)Paul Fleming (1 shared paper)Jennifer King (1 shared paper)
- Journals
- Wind energy science (11 papers)International Journal for Uncertainty Quantification (1 paper)Energies (1 paper)Renewable Energy (1 paper)Electric Power Systems Research (1 paper)
- Partner nations
- United StatesDenmarkGermany
In The Last Decade
Julian Quick
27 papers receiving 233 citations
Peers
Comparison fields: 5 of 22
- Aerospace Engineering 181
- Energy Engineering and Power Technology 7
- Statistics, Probability and Uncertainty 11
- Electrical and Electronic Engineering 48
- Industrial and Manufacturing Engineering 8
Countries citing papers authored by Julian Quick
This map shows the geographic impact of Julian Quick'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 Julian Quick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julian Quick more than expected).
Fields of papers citing papers by Julian Quick
This network shows the impact of papers produced by Julian Quick. 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 Julian Quick. The network helps show where Julian Quick may publish in the future.
Co-authors
The 25 scholars most cited alongside Julian Quick, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 45 | |
| 2 | 2020 | 34 | |
| 3 | 2023 | 24 | |
| 4 | 2023 | 19 | |
| 5 | 2024 | 16 | |
| 6 | 2016 | 15 | |
| 7 | 2024 | 14 | |
| 8 | 2025 | 13 | |
| 9 | 2019 | 7 | |
| 10 | 2019 | 7 | |
| 11 | 2022 | 6 | |
| 12 | 2016 | 5 | |
| 13 | 2021 | 5 | |
| 14 | 2024 | 5 | |
| 15 | 2022 | 3 | |
| 16 | 2024 | 3 | |
| 17 | 2024 | 3 | |
| 18 | 2025 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2024 | 2 |
About Julian Quick
Julian Quick is a scholar working on Aerospace Engineering, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Electrical and Electronic Engineering, having authored 32 papers that have together received 240 indexed citations. Recurring topics across this work include Wind Energy Research and Development (24 papers), Model Reduction and Neural Networks (4 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Electric Power System Optimization (3 papers), Wind Turbine Control Systems (3 papers), Probabilistic and Robust Engineering Design (2 papers), Digital Transformation in Industry (2 papers) and Integrated Energy Systems Optimization (2 papers). The work is most often cited by research in Aerospace Engineering (181 citations), Energy Engineering and Power Technology (7 citations), Statistics, Probability and Uncertainty (11 citations), Electrical and Electronic Engineering (48 citations) and Industrial and Manufacturing Engineering (8 citations). Julian Quick has collaborated with scholars based in United States, Denmark and Germany. Frequent co-authors include Katherine Dykes, Ryan King, Pierre-Elouan Mikael Réthoré, Andrew Ning, Peter E. Hamlington, Jennifer R. Annoni, Paul Fleming, Jennifer King, Peter A Graf and Jason Fields. Their work appears in journals such as Wind energy science, International Journal for Uncertainty Quantification, Energies, Renewable Energy and Electric Power Systems Research.
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.