M. J. Irwin

835 total citations
11 papers, 420 citations indexed

About

M. J. Irwin is a scholar working on Astronomy and Astrophysics, Instrumentation and Oncology. According to data from OpenAlex, M. J. Irwin has authored 11 papers receiving a total of 420 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Astronomy and Astrophysics, 4 papers in Instrumentation and 2 papers in Oncology. Recurrent topics in M. J. Irwin's work include Stellar, planetary, and galactic studies (7 papers), Astronomy and Astrophysical Research (4 papers) and Gamma-ray bursts and supernovae (3 papers). M. J. Irwin is often cited by papers focused on Stellar, planetary, and galactic studies (7 papers), Astronomy and Astrophysical Research (4 papers) and Gamma-ray bursts and supernovae (3 papers). M. J. Irwin collaborates with scholars based in United Kingdom, United States and France. M. J. Irwin's co-authors include B. Letarte, A. Helmi, A. Kaufer, P. Jablonka, G. Battaglia, V. Hill, Kim A. Venn, T. Szeifert, P. François and Eline Tolstoy and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Annals of Oncology.

In The Last Decade

M. J. Irwin

9 papers receiving 406 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. J. Irwin United Kingdom	6	322	178	45	43	37	11	420
N. A. Walton United Kingdom	17	576 1.8×	200 1.1×	65 1.4×	53 1.2×	42 1.1×	82	736
J. Davies United Kingdom	10	413 1.3×	211 1.2×	11 0.2×	26 0.6×	4 0.1×	19	532
David Adler United States	14	186 0.6×	64 0.4×	6 0.1×	46 1.1×	14 0.4×	37	564
Sang Chul Kim South Korea	17	660 2.0×	266 1.5×	8 0.2×	14 0.3×	2 0.1×	57	829
F. Elsner United States	10	190 0.6×	17 0.1×	45 1.0×	7 0.2×	7 0.2×	19	296
Monica Barrera United Kingdom	12	326 1.0×	167 0.9×	7 0.2×	14 0.3×	8 0.2×	14	401
M. E. C. Swanson United States	4	166 0.5×	86 0.5×	15 0.3×	66 1.5×		4	307
Darryl Wright United States	7	69 0.2×	21 0.1×	63 1.4×	89 2.1×	121 3.3×	13	326
S. Muneer India	10	323 1.0×	83 0.5×	9 0.2×	20 0.5×	3 0.1×	52	366
M. Filho Portugal	11	395 1.2×	159 0.9×	118 2.6×	148 3.4×	32 0.9×	30	649

Countries citing papers authored by M. J. Irwin

Since Specialization

Citations

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

Fields of papers citing papers by M. J. Irwin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. J. Irwin. 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 M. J. Irwin. The network helps show where M. J. Irwin may publish in the future.

Co-authorship network of co-authors of M. J. Irwin

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

All Works

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11 of 11 papers shown

Irwin, M. J., et al.. (2019). The WEAVE Core Processing System at CASU. 606–606.

Ali, Hager R., A. Dariush, Jeremy Thomas, et al.. (2017). Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial. Annals of Oncology. 28(8). 1832–1835. 31 indexed citations

Ali, H. Raza, Aliakbar Dariush, Elena Provenzano, et al.. (2016). Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Research. 18(1). 21–21. 64 indexed citations

Picó, Sergio, Chris Benn, S. C. Trager, et al.. (2016). Design of the calibration unit for the WEAVE multi-object spectrograph at the WHT. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9908. 99088R–99088R.

Lemasle, B., Thomas de Boer, V. Hill, et al.. (2014). VLT/FLAMES spectroscopy of red giant branch stars in the Fornax dwarf spheroidal galaxy. Astronomy and Astrophysics. 572. A88–A88. 48 indexed citations

Bate, N. F., A. R. Conn, B. McMonigal, et al.. (2013). Major substructure in the M31 outer halo: the South-West Cloud★. Monthly Notices of the Royal Astronomical Society. 437(4). 3362–3372. 17 indexed citations

Amanullah, R., V. Stanishev, A. Goobar, et al.. (2008). Light curves of five type Ia supernovae at intermediate redshift. Astronomy and Astrophysics. 486(2). 375–382. 15 indexed citations

Balland, C., M. Mouchet, R. Pain, et al.. (2005). Spectroscopy of twelve type\n Ia supernovae at intermediate redshift. Springer Link (Chiba Institute of Technology). 4 indexed citations

Tolstoy, Eline, M. J. Irwin, A. Helmi, et al.. (2004). Two Distinct Ancient Components in the Sculptor Dwarf Spheroidal Galaxy: First Results from the Dwarf Abundances and Radial Velocities Team. The Astrophysical Journal. 617(2). L119–L122. 233 indexed citations

10.

Meusinger, H., et al.. (2002). QSOs from a Variability-and-Proper Motion Survey. International Astronomical Union Colloquium. 184. 69–74. 3 indexed citations

11.

Harris, Hugh C., H. H. Guetter, Jeffrey R. Pier, et al.. (1992). A search for QSOs behind globular clusters. The Astronomical Journal. 104. 53–53. 5 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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