Supatcha Chaimatanan

539 total citations
10 papers, 99 citations indexed

About

Supatcha Chaimatanan is a scholar working on Aerospace Engineering, General Economics, Econometrics and Finance and Industrial and Manufacturing Engineering. According to data from OpenAlex, Supatcha Chaimatanan has authored 10 papers receiving a total of 99 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Aerospace Engineering, 5 papers in General Economics, Econometrics and Finance and 3 papers in Industrial and Manufacturing Engineering. Recurrent topics in Supatcha Chaimatanan's work include Air Traffic Management and Optimization (8 papers), Aviation Industry Analysis and Trends (5 papers) and Vehicle Routing Optimization Methods (3 papers). Supatcha Chaimatanan is often cited by papers focused on Air Traffic Management and Optimization (8 papers), Aviation Industry Analysis and Trends (5 papers) and Vehicle Routing Optimization Methods (3 papers). Supatcha Chaimatanan collaborates with scholars based in France, Thailand and Singapore. Supatcha Chaimatanan's co-authors include Daniel Delahaye, Marcel Mongeau, Sameer Alam, Manuel Soler, Daniel Delahaye, Éric Féron, Ángel G. Fernández, Stefano Bonelli, Raouf Hamzaoui and Rosa María Arnaldo Valdés and has published in prestigious journals such as IEEE Computational Intelligence Magazine, Aerospace and Journal of Aerospace Information Systems.

In The Last Decade

Supatcha Chaimatanan

10 papers receiving 95 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Supatcha Chaimatanan France 5 90 39 19 14 14 10 99
Jessica Rhodes Australia 3 58 0.6× 17 0.4× 3 0.2× 13 0.9× 4 0.3× 5 92
Frank Bussink United States 9 247 2.7× 59 1.5× 26 1.4× 60 4.3× 3 0.2× 27 275
Kyle Treleaven United States 5 25 0.3× 11 0.3× 12 0.6× 37 2.6× 30 2.1× 8 115
Brian T. Baxley United States 10 304 3.4× 73 1.9× 8 0.4× 57 4.1× 3 0.2× 38 330
Richard Coppenbarger United States 8 335 3.7× 110 2.8× 26 1.4× 60 4.3× 3 0.2× 29 354
Blake Wulfe United States 5 17 0.2× 2 0.1× 40 2.1× 46 3.3× 3 0.2× 6 131
Stefan Breuers Germany 3 22 0.2× 80 4.2× 12 0.9× 2 0.1× 3 104
V. Vaquero Spain 5 27 0.3× 55 2.9× 6 0.4× 4 0.3× 7 80
Eugene Gilbo United States 6 324 3.6× 251 6.4× 1 0.1× 83 5.9× 10 0.7× 15 344
Олексій Коломійцев Ukraine 7 77 0.9× 8 0.2× 7 0.5× 2 0.1× 95 202

Countries citing papers authored by Supatcha Chaimatanan

Since Specialization
Citations

This map shows the geographic impact of Supatcha Chaimatanan'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 Supatcha Chaimatanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Supatcha Chaimatanan more than expected).

Fields of papers citing papers by Supatcha Chaimatanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Supatcha Chaimatanan. 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 Supatcha Chaimatanan. The network helps show where Supatcha Chaimatanan may publish in the future.

Co-authorship network of co-authors of Supatcha Chaimatanan

This figure shows the co-authorship network connecting the top 25 collaborators of Supatcha Chaimatanan. A scholar is included among the top collaborators of Supatcha Chaimatanan 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 Supatcha Chaimatanan. Supatcha Chaimatanan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Valdés, Rosa María Arnaldo, Ángel G. Fernández, Stefano Bonelli, et al.. (2025). Air Traffic Management and Communication over ATN/IPS for Future Datalink Communication. SPIRE - Sciences Po Institutional REpository. 1–10. 1 indexed citations
2.
Delahaye, Daniel, et al.. (2022). Hyperheuristic Approach Based on Reinforcement Learning for Air Traffic Complexity Mitigation. Journal of Aerospace Information Systems. 19(9). 633–648. 12 indexed citations
3.
Delahaye, Daniel, et al.. (2022). Air Traffic Complexity Map Based on Linear Dynamical Systems. Aerospace. 9(5). 230–230. 13 indexed citations
4.
Delahaye, Daniel, et al.. (2021). Selective Simulated Annealing for Large Scale Airspace Congestion Mitigation. Aerospace. 8(10). 288–288. 8 indexed citations
5.
Chaimatanan, Supatcha, et al.. (2018). Mission planning for non-homogeneous Earth observation satellites constellation for disaster response. 2018 SpaceOps Conference. 3 indexed citations
6.
Chaimatanan, Supatcha, et al.. (2018). Large Scale Adaptive 4D Trajectory Planning. SPIRE - Sciences Po Institutional REpository. 203. 1–9. 2 indexed citations
7.
Alam, Sameer, Supatcha Chaimatanan, Daniel Delahaye, & Éric Féron. (2018). Metaheuristic Approach for Distributed Trajectory Planning for European Functional Airspace Blocks. HAL (Le Centre pour la Communication Scientifique Directe). 26(3). 81–93. 2 indexed citations
8.
Chaimatanan, Supatcha, et al.. (2017). Geo-Information platform for visualisation, analysis and optimization for aviation. 9. 1–4. 1 indexed citations
9.
Chaimatanan, Supatcha, Daniel Delahaye, & Marcel Mongeau. (2015). Aircraft 4D Trajectories Planning Under Uncertainties. HAL (Le Centre pour la Communication Scientifique Directe). 51–58. 13 indexed citations
10.
Chaimatanan, Supatcha, Daniel Delahaye, & Marcel Mongeau. (2014). A Hybrid Metaheuristic Optimization Algorithm for Strategic Planning of 4D Aircraft Trajectories at the Continental Scale. IEEE Computational Intelligence Magazine. 9(4). 46–61. 44 indexed citations

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.

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