M. Sullivan

32.4k total citations
115 papers, 3.2k citations indexed

About

M. Sullivan is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Instrumentation. According to data from OpenAlex, M. Sullivan has authored 115 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Astronomy and Astrophysics, 27 papers in Nuclear and High Energy Physics and 21 papers in Instrumentation. Recurrent topics in M. Sullivan's work include Gamma-ray bursts and supernovae (85 papers), Stellar, planetary, and galactic studies (45 papers) and Astrophysical Phenomena and Observations (37 papers). M. Sullivan is often cited by papers focused on Gamma-ray bursts and supernovae (85 papers), Stellar, planetary, and galactic studies (45 papers) and Astrophysical Phenomena and Observations (37 papers). M. Sullivan collaborates with scholars based in United Kingdom, United States and Israel. M. Sullivan's co-authors include D. A. Howell, P. Nugent, A. Gal‐Yam, Richard S. Ellis, R. G. Carlberg, K. Maguire, P. A. Mazzali, C. J. Pritchet, I. Hook and A. Conley and has published in prestigious journals such as Nature, Journal of Clinical Investigation and The Astrophysical Journal.

In The Last Decade

M. Sullivan

106 papers receiving 3.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Sullivan United Kingdom 33 3.0k 970 423 90 43 115 3.2k
Lifan Wang United States 30 2.6k 0.8× 903 0.9× 196 0.5× 106 1.2× 110 2.6× 109 2.8k
En‐Wei Liang China 34 3.9k 1.3× 1.6k 1.6× 248 0.6× 17 0.2× 71 1.7× 264 4.1k
Will M. Farr United States 37 4.4k 1.5× 946 1.0× 260 0.6× 25 0.3× 175 4.1× 93 4.7k
Emmanuel Momjian United States 26 1.7k 0.6× 554 0.6× 319 0.8× 15 0.2× 140 3.3× 133 1.8k
J. Sollerman Sweden 45 5.2k 1.7× 1.7k 1.8× 366 0.9× 4 0.0× 59 1.4× 192 5.2k
Li‐Zhi Fang China 19 861 0.3× 250 0.3× 116 0.3× 18 0.2× 56 1.3× 112 1.1k
J. M. Diego Spain 26 1.7k 0.6× 425 0.4× 505 1.2× 5 0.1× 205 4.8× 101 1.9k
F. Grundahl Denmark 31 2.9k 1.0× 427 0.4× 1.6k 3.7× 13 0.1× 83 1.9× 104 3.0k
M. A. Zwaan Germany 29 2.7k 0.9× 688 0.7× 887 2.1× 4 0.0× 85 2.0× 110 2.8k
Nozomu Tominaga Japan 33 4.2k 1.4× 947 1.0× 881 2.1× 4 0.0× 58 1.3× 120 4.3k

Countries citing papers authored by M. Sullivan

Since Specialization
Citations

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

Fields of papers citing papers by M. Sullivan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Sullivan

This figure shows the co-authorship network connecting the top 25 collaborators of M. Sullivan. A scholar is included among the top collaborators of M. Sullivan 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. Sullivan. M. Sullivan 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.
Lukkes, Jodi L., M. Sullivan, Nathan Cunningham, et al.. (2025). A haploinsufficiency restoration strategy corrects neurobehavioral deficits in Nf1+/– mice. Journal of Clinical Investigation. 135(13). 1 indexed citations
2.
Hook, I., C. Frohmaier, G. Dimitriadis, et al.. (2025). Testing and combining transient spectral classification tools on 4MOST-like blended spectra. Monthly Notices of the Royal Astronomical Society. 543(1). 247–272.
3.
Pareek, Nilesh, C. Frohmaier, M. Smith, et al.. (2023). A machine learning algorithm to predict a culprit lesion after out of hospital cardiac arrest. Catheterization and Cardiovascular Interventions. 102(1). 80–90. 2 indexed citations
4.
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
5.
Graham, M. L., Chelsea Harris, P. Nugent, et al.. (2019). Delayed Circumstellar Interaction for Type Ia SN 2015cp Revealed by an HST Ultraviolet Imaging Survey. The Astrophysical Journal. 871(1). 62–62. 26 indexed citations
6.
Jaeger, Thomas de, S. González–Gaitán, M. Hamuy, et al.. (2017). A Type II Supernova Hubble Diagram from the CSP-I, SDSS-II, and SNLS Surveys. Americanae (AECID Library). 11 indexed citations
7.
Karamehmetoglu, E., F. Taddia, J. Sollerman, et al.. (2017). OGLE-2014-SN-131: A long-rising Type Ibn supernova from a massive progenitor. Astronomy and Astrophysics. 602. A93–A93. 12 indexed citations
8.
Lyman, J., D. Homan, K. Maguire, et al.. (2017). LIGO/VIRGO G298048: ePESSTO optical spectra of the candidate optical/NIR counterpart of the gravitational wave G298048 in NGC4993.. GRB Coordinates Network. 21582. 1. 1 indexed citations
9.
Corsi, A., A. Gal‐Yam, S. R. Kulkarni, et al.. (2016). RADIO OBSERVATIONS OF A SAMPLE OF BROAD-LINE TYPE IC SUPERNOVAE DISCOVERED BY PTF/IPTF: A SEARCH FOR RELATIVISTIC EXPLOSIONS. The Astrophysical Journal. 830(1). 42–42. 20 indexed citations
10.
Strotjohann, N. L., E. O. Ofek, A. Gal‐Yam, et al.. (2015). SEARCH FOR PRECURSOR ERUPTIONS AMONG TYPE IIB SUPERNOVAE. The Astrophysical Journal. 811(2). 117–117. 13 indexed citations
11.
González–Gaitán, S., Nozomu Tominaga, Juan Molina, et al.. (2015). The rise-time of Type II supernovae. Monthly Notices of the Royal Astronomical Society. 451(2). 2212–2229. 57 indexed citations
12.
Monard, L. A. G., M. Fraser, M. Smith, et al.. (2015). Supernova 2015F in NGC 2442 = Psn J07361576-6930230. 4081. 1. 1 indexed citations
13.
Mazzali, P. A., M. Sullivan, Stephan Hachinger, et al.. (2014). Hubble Space Telescope spectra of the Type Ia supernova SN 2011fe: a tail of low-density, high-velocity material with Z < Z⊙. Monthly Notices of the Royal Astronomical Society. 439(2). 1959–1979. 73 indexed citations
14.
Ofek, E. O., I. Arcavi, D. Tal, et al.. (2014). INTERACTION-POWERED SUPERNOVAE: RISE-TIME VERSUS PEAK-LUMINOSITY CORRELATION AND THE SHOCK-BREAKOUT VELOCITY. The Astrophysical Journal. 788(2). 154–154. 39 indexed citations
15.
Inserra, C., R. Scalzo, M. Fraser, et al.. (2013). SN2012ca: a stripped envelope core-collapse SN interacting with dense circumstellar medium. Monthly Notices of the Royal Astronomical Society Letters. 437(1). L51–L55. 13 indexed citations
16.
Monard, L. A. G., A. Morales-Garoffolo, N. Elias–Rosa, et al.. (2013). Supernova 2013L in ESO 216-39 = Psn J11452955-5035531. 3392. 1. 2 indexed citations
17.
Fraser, M., R. Kotak, A. Pastorello, et al.. (2013). First observations of the reappearance of SN 2009ip with PESSTO. ATel. 4953. 1. 1 indexed citations
18.
Smartt, S. J., S. Valenti, M. Fraser, et al.. (2013). PESSTO: The Public ESO Spectroscopic Survey of Transient Objects. Max Planck Digital Library. 154. 50–52. 4 indexed citations
19.
Bronder, T. J., I. Hook, D. A. Howell, et al.. (2007). Quantitative Spectroscopy of Distant Type Ia Supernovae. AIP conference proceedings. 415–420. 1 indexed citations
20.
Coyle, Lorcan, et al.. (2006). Sensor Fusion-Based Middleware for Smart Homes. eCite Digital Repository (University of Tasmania). 11 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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