Mike Walmsley

1.5k total citations
24 papers, 814 citations indexed

About

Mike Walmsley is a scholar working on Astronomy and Astrophysics, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Mike Walmsley has authored 24 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Astronomy and Astrophysics, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Mike Walmsley's work include Galaxies: Formation, Evolution, Phenomena (14 papers), Advanced Vision and Imaging (6 papers) and Stellar, planetary, and galactic studies (4 papers). Mike Walmsley is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (14 papers), Advanced Vision and Imaging (6 papers) and Stellar, planetary, and galactic studies (4 papers). Mike Walmsley collaborates with scholars based in United Kingdom, United States and Canada. Mike Walmsley's co-authors include Karen P. Day, Michelle Packer, Raymond Paru, Moses Lagog, Lisa Ranford‐Cartwright, R. E. L. Paul, Chris Lintott, Karen L. Masters, Sandor Kruk and Brooke Simmons and has published in prestigious journals such as Science, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Mike Walmsley

22 papers receiving 751 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mike Walmsley United Kingdom 12 361 265 128 111 100 24 814
David Tcheng United States 14 77 0.2× 119 0.4× 10 0.1× 55 0.5× 102 1.0× 36 872
P. W. Draper United Kingdom 24 41 0.1× 1.0k 3.9× 40 0.3× 375 3.4× 103 1.0× 111 2.3k
Anthony L. Piro United States 32 73 0.2× 2.5k 9.6× 217 1.7× 170 1.5× 7 0.1× 92 3.2k
Christopher R. Stephens Mexico 22 233 0.6× 232 0.9× 98 0.8× 1 0.0× 95 0.9× 126 1.5k
Xuemin Jin United States 21 30 0.1× 74 0.3× 153 1.2× 5 0.0× 57 0.6× 65 1.2k
Riccardo Murgia Italy 21 45 0.1× 957 3.6× 340 2.7× 58 0.5× 3 0.0× 28 1.4k
Guoliang Lü China 13 233 0.6× 993 3.7× 17 0.1× 173 1.6× 13 0.1× 75 1.4k
George Githinji Kenya 11 104 0.3× 33 0.1× 13 0.1× 7 0.1× 34 0.3× 24 431
Siqing Liu China 21 132 0.4× 1.1k 4.1× 5 0.0× 2 0.0× 19 0.2× 132 1.6k
Steve Henry Australia 13 23 0.1× 211 0.8× 9 0.1× 104 0.9× 83 0.8× 36 735

Countries citing papers authored by Mike Walmsley

Since Specialization
Citations

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

Fields of papers citing papers by Mike Walmsley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mike Walmsley

This figure shows the co-authorship network connecting the top 25 collaborators of Mike Walmsley. A scholar is included among the top collaborators of Mike Walmsley 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 Mike Walmsley. Mike Walmsley 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.
Graaff, R., Berta Margalef-Bentabol, Lingyu Wang, et al.. (2025). Classifying merger stages with adaptive deep learning and cosmological hydrodynamical simulations. Astronomy and Astrophysics. 697. A207–A207.
2.
Nord, B., et al.. (2025). SIDDA: SInkhorn Dynamic Domain Adaptation for image classification with equivariant neural networks. Machine Learning Science and Technology. 1 indexed citations
3.
Holwerda, Benne W., Kevin A. Pimbblet, Sarah Casura, et al.. (2024). The Galaxy Zoo catalogues for Galaxy And Mass Assembly (GAMA) survey. Publications of the Astronomical Society of Australia. 41.
4.
Lochner, Michelle, et al.. (2024). Astronomaly at scale: searching for anomalies amongst 4 million galaxies. Monthly Notices of the Royal Astronomical Society. 529(1). 732–747. 8 indexed citations
5.
Walmsley, Mike, Maddie S. Silcock, Brooke Simmons, et al.. (2024). Galaxy Zoo DESI: large-scale bars as a secular mechanism for triggering AGNs. Monthly Notices of the Royal Astronomical Society. 532(2). 2320–2330. 8 indexed citations
6.
Popp, Jürgen, H. J. Dickinson, S. Serjeant, et al.. (2024). Transfer learning for galaxy feature detection: Finding giant star-forming clumps in low-redshift galaxies using Faster Region-based Convolutional Neural Network. Open Research Online (The Open University). 3(1). 174–197. 1 indexed citations
7.
Merín, B., Brooke Simmons, Mike Walmsley, et al.. (2023). Harnessing the Hubble Space Telescope Archives: A Catalog of 21,926 Interacting Galaxies. The Astrophysical Journal. 948(1). 40–40. 4 indexed citations
8.
Géron, Tobias, Rebecca Smethurst, Chris Lintott, et al.. (2023). Galaxy Zoo: kinematics of strongly and weakly barred galaxies. Monthly Notices of the Royal Astronomical Society. 521(2). 1775–1793. 23 indexed citations
9.
Walmsley, Mike, et al.. (2023). Zoobot: Adaptable Deep Learning Models for GalaxyMorphology. The Journal of Open Source Software. 8(85). 5312–5312. 13 indexed citations
10.
Walmsley, Mike, Tobias Géron, Sandor Kruk, et al.. (2023). Galaxy Zoo DESI: Detailed morphology measurements for 8.7M galaxies in the DESI Legacy Imaging Surveys. Monthly Notices of the Royal Astronomical Society. 526(3). 4768–4786. 23 indexed citations
11.
Bottrell, Connor, Mike Walmsley, Hassen M. Yesuf, et al.. (2023). Galaxy mergers in Subaru HSC-SSP: A deep representation learning approach for identification, and the role of environment on merger incidence. Astronomy and Astrophysics. 679. A142–A142. 15 indexed citations
12.
Scaife, Anna M. M., et al.. (2023). Radio galaxy zoo: towards building the first multipurpose foundation model for radio astronomy with self-supervised learning. Research Explorer (The University of Manchester). 3(1). 19–32. 13 indexed citations
13.
Dickinson, H. J., Vihang Mehta, Claudia Scarlata, et al.. (2022). Galaxy Zoo: Clump Scout – Design and first application of a two-dimensional aggregation tool for citizen science. Monthly Notices of the Royal Astronomical Society. 517(4). 5882–5911. 4 indexed citations
14.
15.
Walmsley, Mike, Chris Lintott, Tobias Géron, et al.. (2021). Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies. Monthly Notices of the Royal Astronomical Society. 509(3). 3966–3988. 111 indexed citations
16.
Walmsley, Mike, Lewis Smith, Chris Lintott, et al.. (2019). Galaxy Zoo: probabilistic morphology through Bayesian CNNs and active learning. Monthly Notices of the Royal Astronomical Society. 491(2). 1554–1574. 86 indexed citations
17.
Gordon, Yjan, Kevin A. Pimbblet, Sugata Kaviraj, et al.. (2019). The Effect of Minor and Major Mergers on the Evolution of Low-excitation Radio Galaxies. The Astrophysical Journal. 878(2). 88–88. 12 indexed citations
18.
Walmsley, Mike, A. M. N. Ferguson, Robert G. Mann, & Chris Lintott. (2018). Identification of low surface brightness tidal features in galaxies using convolutional neural networks. Monthly Notices of the Royal Astronomical Society. 483(3). 2968–2982. 40 indexed citations
19.
Bruce, Marian C., Mary R. Galinski, John W. Barnwell, et al.. (2000). Genetic diversity and dynamics of Plasmodium falciparum and P. vivax populations in multiply infected children with asymptomatic malaria infections in Papua New Guinea. Parasitology. 121(3). 257–272. 126 indexed citations
20.
Paul, R. E. L., Michelle Packer, Mike Walmsley, et al.. (1995). Mating Patterns in Malaria Parasite Populations of Papua New Guinea. Science. 269(5231). 1709–1711. 272 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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