Ian Langmore
- Atmospheric Science top 10%
- Global and Planetary Change top 10%
- Electrical and Electronic Engineering
- Environmental Engineering
- Artificial Intelligence
- Co-authors
- Paul DraxlerP.M. AsbeckGuillaume BalStephan HoyerÁlvaro Sánchez‐GonzálezPeter BattagliaStephan RaspPeter Nørgaard
- Topics
- Numerical methods in inverse problems (5 papers)Magnetic confinement fusion research (4 papers)Meteorological Phenomena and Simulations (3 papers)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Ian Langmore
19 papers receiving 403 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Atmospheric Science 155
- Global and Planetary Change 138
- Electrical and Electronic Engineering 103
- Environmental Engineering 59
- Artificial Intelligence 50
Countries citing papers authored by Ian Langmore
This map shows the geographic impact of Ian Langmore'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 Ian Langmore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Langmore more than expected).
Fields of papers citing papers by Ian Langmore
This network shows the impact of papers produced by Ian Langmore. 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 Ian Langmore. The network helps show where Ian Langmore may publish in the future.
Co-authorship network of co-authors of Ian Langmore
This figure shows the co-authorship network connecting the top 25 collaborators of Ian Langmore. A scholar is included among the top collaborators of Ian Langmore 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 Ian Langmore. Ian Langmore 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 | Neural general circulation models for weather and climatebreakdown → | 153 |
| 3 | WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Modelsbreakdown → | 82 |
| 4 | 13 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | High-fidelity Bayesian inference of transient FRC plasma perturbations in C-2W | 1 |
| 8 | Application of Bayesian inference for reconstruction of FRC plasma state in C-2W | 1 |
| 9 | Reconstruction of fusion plasma state with a Plasma Debugger | 1 |
| 10 | 15 | |
| 11 | 7 | |
| 12 | 13 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 14 | |
| 16 | 6 | |
| 17 | 21 | |
| 18 | 51 | |
| 19 | 30 | |
| 20 | 21 |
About Ian Langmore
Ian Langmore is a scholar working on Acoustics and Ultrasonics, Mathematical Physics and Nuclear and High Energy Physics, having authored 20 papers that have together received 444 indexed citations. Recurring topics across this work include Numerical methods in inverse problems (5 papers), Magnetic confinement fusion research (4 papers) and Meteorological Phenomena and Simulations (3 papers). The work is most often cited by research in Atmospheric Science (155 citations), Global and Planetary Change (138 citations) and Mathematical Physics (49 citations). Ian Langmore has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Paul Draxler, P.M. Asbeck, Guillaume Bal, Stephan Hoyer, Álvaro Sánchez‐González, Peter Battaglia, Stephan Rasp, Peter Nørgaard, Donald F. Kimball and Janni Yuval. Their work appears in journals such as Nature, Journal of Computational Physics and IEEE Transactions on Geoscience and Remote Sensing.
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.