Iain McDonald

5.1k total citations
94 papers, 2.0k citations indexed

About

Iain McDonald is a scholar working on Astronomy and Astrophysics, Instrumentation and Computational Mechanics. According to data from OpenAlex, Iain McDonald has authored 94 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Astronomy and Astrophysics, 45 papers in Instrumentation and 5 papers in Computational Mechanics. Recurrent topics in Iain McDonald's work include Stellar, planetary, and galactic studies (84 papers), Astrophysics and Star Formation Studies (60 papers) and Astronomy and Astrophysical Research (45 papers). Iain McDonald is often cited by papers focused on Stellar, planetary, and galactic studies (84 papers), Astrophysics and Star Formation Studies (60 papers) and Astronomy and Astrophysical Research (45 papers). Iain McDonald collaborates with scholars based in United Kingdom, United States and France. Iain McDonald's co-authors include A. A. Zijlstra, Martha L. Boyer, J. Th. van Loon, G. C. Sloan, L. Decin, A. M. S. Richards, P. Kervella, E. Lagadec, S. Srinivasan and M. Meixner and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Iain McDonald

87 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Iain McDonald United Kingdom 28 2.0k 868 84 68 50 94 2.0k
Martha L. Boyer United States 28 2.1k 1.1× 961 1.1× 63 0.8× 55 0.8× 43 0.9× 77 2.2k
P. Jofré Chile 24 1.6k 0.8× 842 1.0× 77 0.9× 83 1.2× 47 0.9× 60 1.7k
S. Blanco-Cuaresma United States 17 1.1k 0.6× 611 0.7× 64 0.8× 60 0.9× 48 1.0× 39 1.2k
M. J. P. F. G. Monteiro Portugal 21 1.7k 0.9× 737 0.8× 67 0.8× 69 1.0× 27 0.5× 72 1.7k
Bun’ei Sato Japan 27 1.9k 1.0× 678 0.8× 45 0.5× 79 1.2× 56 1.1× 78 1.9k
Natalie M. Batalha United States 21 1.8k 0.9× 564 0.6× 81 1.0× 49 0.7× 64 1.3× 62 1.9k
V. Silva Aguirre Denmark 27 2.3k 1.1× 1.2k 1.3× 97 1.2× 79 1.2× 21 0.4× 69 2.3k
Maria-Rosa L. Cioni Germany 27 2.6k 1.3× 1.2k 1.4× 142 1.7× 115 1.7× 55 1.1× 101 2.7k
D. Pourbaix Belgium 23 1.9k 1.0× 817 0.9× 133 1.6× 71 1.0× 40 0.8× 77 2.0k
Melissa Ness United States 25 2.4k 1.2× 1.2k 1.4× 98 1.2× 126 1.9× 23 0.5× 95 2.5k

Countries citing papers authored by Iain McDonald

Since Specialization
Citations

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

Fields of papers citing papers by Iain McDonald

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iain McDonald

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

All Works

20 of 20 papers shown
1.
Javadi, Atefeh, J. Th. van Loon, Iain McDonald, et al.. (2025). Dusty Stellar Source Classification by Implementing Machine Learning Methods Based on Spectroscopic Observations in the Magellanic Clouds. The Astrophysical Journal. 986(2). 168–168.
2.
Zijlstra, A. A., et al.. (2025). Central-star extinctions towards planetary nebulae. Monthly Notices of the Royal Astronomical Society. 543(3). 3035–3054.
3.
Scher, Sebastian, et al.. (2024). Machine learning based stellar classification with highly sparse photometry data. SHILAP Revista de lepidopterología. 4. 29–29. 1 indexed citations
4.
Uttenthaler, S., S. Shetye, A. Nanni, et al.. (2024). The impact of third dredge-up on the mass loss of Mira variables. Astronomy and Astrophysics. 690. A393–A393. 3 indexed citations
5.
McDonald, Iain, et al.. (2024). PySSED: an automated method of collating and fitting stellar spectral energy distributions. Research Explorer (The University of Manchester). 3(1). 89–107. 6 indexed citations
6.
Scher, Sebastian, et al.. (2024). Machine learning based stellar classification with highly sparse photometry data. Open Research Europe. 4. 29–29. 1 indexed citations
8.
Goldman, Steven, Martha L. Boyer, Julianne J. Dalcanton, et al.. (2022). A Census of Thermally Pulsing AGB Stars in the Andromeda Galaxy and a First Estimate of Their Contribution to the Global Dust Budget. The Astrophysical Journal Supplement Series. 259(2). 41–41. 7 indexed citations
9.
Podlewska-Gaca, E., R. Poleski, P. Bartczak, Iain McDonald, & András Pál. (2021). Determination of Rotation Periods for a Large Sample of Asteroids from the K2 Campaign 9. Repository of the Academy's Library (Library of the Hungarian Academy of Sciences). 4 indexed citations
10.
Javadi, Atefeh, et al.. (2021). The Star Formation History and Dust Production in Andromeda IX. Proceedings of the International Astronomical Union. 17(S373). 242–245. 1 indexed citations
11.
Iskandar, D. N. F. Awang, A. A. Zijlstra, Iain McDonald, et al.. (2020). Classification of Planetary Nebulae through Deep Transfer Learning. Unimas Institutional Repository (Universiti Malaysia Sarawak). 2 indexed citations
12.
Uttenthaler, S., Iain McDonald, Klaus Bernhard, S. Cristallo, & D. Gobrecht. (2019). Interplay between pulsation, mass loss, and third dredge-up: More about Miras with and without technetium. Springer Link (Chiba Institute of Technology). 11 indexed citations
13.
Kraemer, K. E., G. C. Sloan, L. D. Keller, et al.. (2019). Stellar Pulsation and the Production of Dust and Molecules in Galactic Carbon Stars. The Astrophysical Journal. 887(1). 82–82. 6 indexed citations
14.
Zijlstra, A. A., et al.. (2018). Flickering in AGB stars: probing the nature of accreting companions. Monthly Notices of the Royal Astronomical Society. 477(3). 4200–4212. 7 indexed citations
15.
Kervella, P., L. Decin, A. M. S. Richards, et al.. (2017). The close circumstellar environment of Betelgeuse. Astronomy and Astrophysics. 609. A67–A67. 61 indexed citations
16.
Kacharov, N., Paolo Bianchini, Andreas Koch, et al.. (2014). A study of rotating globular clusters : the case of the old, metal-poor globular cluster NGC 4372. Max Planck Institute for Plasma Physics. 31 indexed citations
17.
McDonald, Iain, A. A. Zijlstra, & Martha L. Boyer. (2012). Fundamental parameters and infrared excesses ofHipparcosstars. Monthly Notices of the Royal Astronomical Society. 427(1). 343–357. 159 indexed citations
18.
McDonald, Iain, Martha L. Boyer, J. Th. van Loon, & A. A. Zijlstra. (2011). DUST PRODUCTION AND MASS LOSS IN THE GALACTIC GLOBULAR CLUSTER 47 TUCANAE. The Astrophysical Journal. 730(2). 71–71. 35 indexed citations
19.
McDonald, Iain, J. Th. van Loon, A. K. Dupree, & Martha L. Boyer. (2010). Discovery of long-period variable stars in the very metal-poor globular cluster M15. Monthly Notices of the Royal Astronomical Society. no–no. 17 indexed citations
20.
Boyer, Martha L., Iain McDonald, J. Th. van Loon, et al.. (2009). DUST PRODUCTION AND MASS LOSS IN THE GALACTIC GLOBULAR CLUSTER NGC 362. The Astrophysical Journal. 705(1). 746–757. 34 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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