Michelle Lochner

1.2k total citations
21 papers, 336 citations indexed

About

Michelle Lochner is a scholar working on Astronomy and Astrophysics, Instrumentation and Nuclear and High Energy Physics. According to data from OpenAlex, Michelle Lochner has authored 21 papers receiving a total of 336 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Astronomy and Astrophysics, 7 papers in Instrumentation and 6 papers in Nuclear and High Energy Physics. Recurrent topics in Michelle Lochner's work include Gamma-ray bursts and supernovae (11 papers), Astronomy and Astrophysical Research (7 papers) and Galaxies: Formation, Evolution, Phenomena (7 papers). Michelle Lochner is often cited by papers focused on Gamma-ray bursts and supernovae (11 papers), Astronomy and Astrophysical Research (7 papers) and Galaxies: Formation, Evolution, Phenomena (7 papers). Michelle Lochner collaborates with scholars based in South Africa, United Kingdom and United States. Michelle Lochner's co-authors include Hiranya V. Peiris, Jason D. McEwen, O. Lahav, Andrew Pontzen, Bruce A. Bassett, Nadeem Oozeer, Sara Webb, Daniel Muthukrishna, L. Rudnick and Etienne Vos and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, The Astrophysical Journal Supplement Series and Astronomy and Astrophysics.

In The Last Decade

Michelle Lochner

21 papers receiving 319 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michelle Lochner South Africa 11 241 79 56 50 38 21 336
Kai Polsterer Germany 11 206 0.9× 40 0.5× 58 1.0× 45 0.9× 46 1.2× 36 317
Miles Cranmer United States 12 209 0.9× 55 0.7× 44 0.8× 111 2.2× 14 0.4× 23 363
J. C. Maureira Chile 10 209 0.9× 41 0.5× 56 1.0× 20 0.4× 19 0.5× 22 347
Alexander Gray 4 249 1.0× 38 0.5× 88 1.6× 34 0.7× 19 0.5× 8 326
K. Barbary United States 9 320 1.3× 47 0.6× 127 2.3× 25 0.5× 22 0.6× 19 430
Julie Banfield Australia 16 603 2.5× 272 3.4× 100 1.8× 24 0.5× 43 1.1× 28 650
Bruno Régaldo-Saint Blancard United States 10 175 0.7× 38 0.5× 39 0.7× 32 0.6× 14 0.4× 14 237
Timothy J. Galvin Australia 13 500 2.1× 255 3.2× 34 0.6× 19 0.4× 43 1.1× 51 555
S. V. White South Africa 14 522 2.2× 260 3.3× 123 2.2× 24 0.5× 23 0.6× 29 561
N Jeffrey United Kingdom 9 156 0.6× 31 0.4× 38 0.7× 73 1.5× 14 0.4× 15 260

Countries citing papers authored by Michelle Lochner

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Lochner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle Lochner

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Lochner. A scholar is included among the top collaborators of Michelle Lochner 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 Michelle Lochner. Michelle Lochner 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.
Lintott, Chris, Michelle Lochner, P. A. Woudt, et al.. (2025). Finding radio transients with anomaly detection and active learning based on volunteer classifications. Monthly Notices of the Royal Astronomical Society. 538(3). 1397–1414. 2 indexed citations
2.
Lochner, Michelle & L. Rudnick. (2025). Astronomaly Protege: Discovery through Human-machine Collaboration. The Astronomical Journal. 169(3). 121–121. 2 indexed citations
3.
Lochner, Michelle, et al.. (2024). Enabling unsupervised discovery in astronomical images through self-supervised representations. Monthly Notices of the Royal Astronomical Society. 530(1). 1274–1295. 8 indexed citations
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.
Pollo, A., et al.. (2024). TEGLIE: Transformer encoders as strong gravitational lens finders in KiDS. Astronomy and Astrophysics. 688. A34–A34. 4 indexed citations
6.
Gris, Philippe, Humna Awan, I. Hook, et al.. (2023). Designing an Optimal LSST Deep Drilling Program for Cosmology with Type Ia Supernovae. The Astrophysical Journal Supplement Series. 264(1). 22–22. 6 indexed citations
7.
Peiris, Hiranya V., et al.. (2023). Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification. The Astrophysical Journal Supplement Series. 265(2). 43–43. 3 indexed citations
8.
Muthukrishna, Daniel, Kaisey S. Mandel, Michelle Lochner, Sara Webb, & Gautham Narayan. (2022). Real-time detection of anomalies in large-scale transient surveys. Monthly Notices of the Royal Astronomical Society. 517(1). 393–419. 16 indexed citations
9.
Peiris, Hiranya V., et al.. (2021). Considerations for optimizing photometric classification of supernovae from the Rubin Observatory. arXiv (Cornell University). 12 indexed citations
10.
Webb, Sara, Chris Flynn, Jeff Cooke, et al.. (2021). The Deeper, Wider, Faster programme: exploring stellar flare activity with deep, fast cadenced DECam imaging via machine learning. Monthly Notices of the Royal Astronomical Society. 506(2). 2089–2103. 12 indexed citations
11.
Lochner, Michelle, Bruce A. Bassett, Hiranya V. Peiris, et al.. (2020). Classification of multiwavelength transients with machine learning. Monthly Notices of the Royal Astronomical Society. 502(1). 206–224. 11 indexed citations
12.
Webb, Sara, Michelle Lochner, Daniel Muthukrishna, et al.. (2020). Unsupervised machine learning for transient discovery in deeper, wider, faster light curves. Monthly Notices of the Royal Astronomical Society. 498(3). 3077–3094. 20 indexed citations
13.
Bassett, Bruce A., et al.. (2020). Bayesian anomaly detection and classification for noisy data. International Journal of Hybrid Intelligent Systems. 16(4). 207–222. 3 indexed citations
14.
Vos, Etienne, et al.. (2019). DeepSource: point source detection using deep learning. Monthly Notices of the Royal Astronomical Society. 484(2). 2793–2806. 30 indexed citations
15.
Lochner, Michelle, et al.. (2018). Radio galaxy shape measurement with Hamiltonian Monte Carlo in the visibility domain. Monthly Notices of the Royal Astronomical Society. 482(1). 1096–1109. 5 indexed citations
16.
Peiris, Hiranya V., et al.. (2018). Machine learning cosmological structure formation. Monthly Notices of the Royal Astronomical Society. 479(3). 3405–3414. 46 indexed citations
17.
Lochner, Michelle, et al.. (2017). zBEAMS: a unified solution for supernova cosmology with redshift uncertainties. Journal of Cosmology and Astroparticle Physics. 2017(10). 36–36. 10 indexed citations
18.
Lochner, Michelle & Bruce A. Bassett. (2017). Machine Learning for Transient Classification. Proceedings of the International Astronomical Union. 14(S339). 274–274. 2 indexed citations
19.
Lochner, Michelle, et al.. (2016). PHOTOMETRIC SUPERNOVA CLASSIFICATION WITH MACHINE LEARNING. The Astrophysical Journal Supplement Series. 225(2). 31–31. 99 indexed citations
20.
Lochner, Michelle, Iniyan Natarajan, Jonathan Zwart, et al.. (2015). Bayesian inference for radio observations. Monthly Notices of the Royal Astronomical Society. 450(2). 1308–1319. 19 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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