Nicholas Burgess
- Computational Mechanics top 5%
- Finance top 10%
- Statistical and Nonlinear Physics top 10%
- Applied Mathematics top 10%
- Mechanics of Materials
- Co-authors
- Dimitri J. MavriplisKhosro ShahbaziSteven R. AllmarasLi WangKyle AndersonMarshall C. GalbraithDavid DarmofalJames G. Coder
- Topics
- Computational Fluid Dynamics and Aerodynamics (18 papers)Advanced Numerical Methods in Computational Mathematics (15 papers)Stochastic processes and financial applications (10 papers)
- Partner nations
- United KingdomUnited StatesNorway
In The Last Decade
Nicholas Burgess
47 papers receiving 417 citations
Peers
Comparison fields: 5 of 43
- Computational Mechanics 333
- Finance 50
- Statistical and Nonlinear Physics 48
- Applied Mathematics 47
- Mechanics of Materials 40
Countries citing papers authored by Nicholas Burgess
This map shows the geographic impact of Nicholas Burgess'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 Nicholas Burgess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Burgess more than expected).
Fields of papers citing papers by Nicholas Burgess
This network shows the impact of papers produced by Nicholas Burgess. 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 Nicholas Burgess. The network helps show where Nicholas Burgess may publish in the future.
Co-authorship network of co-authors of Nicholas Burgess
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Burgess. A scholar is included among the top collaborators of Nicholas Burgess based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nicholas Burgess. Nicholas Burgess is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 47 | |
| 16 | An adaptive discontinuous Galerkin solver for aerodynamic flows | 26 |
| 17 | 1 | |
| 18 | 12 | |
| 19 | 32 | |
| 20 | 2 |
About Nicholas Burgess
Nicholas Burgess is a scholar working on Finance, Computational Mechanics and Strategy and Management, having authored 50 papers that have together received 428 indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (18 papers), Advanced Numerical Methods in Computational Mathematics (15 papers) and Stochastic processes and financial applications (10 papers). The work is most often cited by research in Computational Mechanics (333 citations), Numerical Analysis (28 citations) and Finance (50 citations). Nicholas Burgess has collaborated with scholars based in United Kingdom, United States and Norway. Frequent co-authors include Dimitri J. Mavriplis, Khosro Shahbazi, Steven R. Allmaras, Li Wang, Kyle Anderson, Marshall C. Galbraith, David Darmofal, James G. Coder, Anirban Garai and Kannan N. Premnath. Their work appears in journals such as Journal of Computational Physics, AIAA Journal and Computational Geosciences.
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.