J. McIver

35.2k total citations
23 papers, 358 citations indexed

About

J. McIver is a scholar working on Astronomy and Astrophysics, Oceanography and Geophysics. According to data from OpenAlex, J. McIver has authored 23 papers receiving a total of 358 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Astronomy and Astrophysics, 5 papers in Oceanography and 5 papers in Geophysics. Recurrent topics in J. McIver's work include Pulsars and Gravitational Waves Research (20 papers), Gamma-ray bursts and supernovae (12 papers) and Geophysics and Gravity Measurements (5 papers). J. McIver is often cited by papers focused on Pulsars and Gravitational Waves Research (20 papers), Gamma-ray bursts and supernovae (12 papers) and Geophysics and Gravity Measurements (5 papers). J. McIver collaborates with scholars based in Canada, United States and United Kingdom. J. McIver's co-authors include Will M. Farr, I. M. Romero-Shaw, T. B. Littenberg, G. Ashton, A. M. Knee, D. Davis, L. K. Nuttall, F. Di Renzo, E. Thrane and P. D. Lasky and has published in prestigious journals such as The Astrophysical Journal, Physical review. D and Classical and Quantum Gravity.

In The Last Decade

J. McIver

21 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. McIver Canada 9 336 108 67 42 22 23 358
V. Gayathri United States 12 638 1.9× 79 0.7× 43 0.6× 106 2.5× 14 0.6× 26 662
G. Riemenschneider Italy 7 472 1.4× 117 1.1× 81 1.2× 76 1.8× 12 0.5× 8 481
S. Kandhasamy United States 8 251 0.7× 70 0.6× 49 0.7× 32 0.8× 32 1.5× 12 278
S. Klimenko United States 6 319 0.9× 70 0.6× 32 0.5× 53 1.3× 10 0.5× 10 330
D. M. Wysocki United States 12 686 2.0× 58 0.5× 35 0.5× 114 2.7× 12 0.5× 16 705
Natalia Korsakova France 8 212 0.6× 29 0.3× 44 0.7× 48 1.1× 35 1.6× 15 247
C. V. Kalaghatgi United Kingdom 7 333 1.0× 59 0.5× 52 0.8× 61 1.5× 8 0.4× 9 343
Reetika Dudi Germany 10 553 1.6× 167 1.5× 132 2.0× 72 1.7× 17 0.8× 10 561
Hang Yu United States 15 433 1.3× 126 1.2× 60 0.9× 54 1.3× 18 0.8× 29 489
Edward Fauchon-Jones United Kingdom 5 322 1.0× 56 0.5× 50 0.7× 57 1.4× 6 0.3× 7 329

Countries citing papers authored by J. McIver

Since Specialization
Citations

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

Fields of papers citing papers by J. McIver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. McIver

This figure shows the co-authorship network connecting the top 25 collaborators of J. McIver. A scholar is included among the top collaborators of J. McIver 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 J. McIver. J. McIver 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.
Naoz, Smadar, Alvin K. Y. Li, Bence Kocsis, et al.. (2025). Extracting astrophysical information of highly eccentric binaries in the millihertz gravitational wave band. Physical review. D. 111(4). 3 indexed citations
2.
Raza, N., M. Chan, Daryl Haggard, et al.. (2025). GWSkyNet-Multi. II. An Updated Machine Learning Model for Rapid Classification of Gravitational-wave Events. The Astrophysical Journal. 992(1). 152–152.
3.
Knee, A. M., E. Goetz, J. McIver, et al.. (2024). Search for continuous gravitational waves directed at subthreshold radiometer candidates in O3 LIGO data. Physical review. D. 109(6). 3 indexed citations
4.
Chan, M., J. McIver, A. Mahabal, et al.. (2024). GWSkyNet. II. A Refined Machine-learning Pipeline for Real-time Classification of Public Gravitational Wave Alerts. The Astrophysical Journal. 972(1). 50–50. 2 indexed citations
5.
Ng, Raymond T., et al.. (2024). GSpyNetTree: a signal-vs-glitch classifier for gravitational-wave event candidates. Classical and Quantum Gravity. 41(8). 85007–85007. 6 indexed citations
6.
Knee, A. M., et al.. (2023). Waves in a forest: a random forest classifier to distinguish between gravitational waves and detector glitches. Classical and Quantum Gravity. 40(23). 235008–235008. 2 indexed citations
7.
Rieger, Georg W., et al.. (2023). Getting More Out of Midterm Assessments. The Physics Teacher. 61(3). 207–209.
8.
Knee, A. M., I. M. Romero-Shaw, P. D. Lasky, J. McIver, & E. Thrane. (2022). A Rosetta Stone for Eccentric Gravitational Waveform Models. The Astrophysical Journal. 936(2). 172–172. 35 indexed citations
9.
Knee, A. M., J. McIver, & M. Cabero. (2022). Prospects for Measuring Off-axis Spins of Binary Black Holes with Plus-era Gravitational-wave Detectors. The Astrophysical Journal. 928(1). 21–21. 5 indexed citations
10.
Davis, D., T. B. Littenberg, I. M. Romero-Shaw, et al.. (2022). Subtracting glitches from gravitational-wave detector data during the third LIGO-Virgo observing run. Classical and Quantum Gravity. 39(24). 245013–245013. 45 indexed citations
11.
Rieger, Georg W., et al.. (2022). Supporting Students’ Self-Regulated Learning in an Introductory Physics Course. The Physics Teacher. 61(1). 18–21. 1 indexed citations
12.
Ng, Raymond T., et al.. (2022). UniMAP: model-free detection of unclassified noise transients in LIGO-Virgo data using the temporal outlier factor. Classical and Quantum Gravity. 39(13). 135011–135011. 2 indexed citations
13.
Macas, R., L. K. Nuttall, D. Davis, et al.. (2022). Impact of noise transients on low latency gravitational-wave event localization. Physical review. D. 105(10). 24 indexed citations
14.
Ashton, G., et al.. (2022). Parameterised population models of transient non-Gaussian noise in the LIGO gravitational-wave detectors. Classical and Quantum Gravity. 39(17). 175004–175004. 17 indexed citations
15.
Cabero, M., et al.. (2021). GWSkyNet-Multi: A Machine Learning Multi-Class Classifier for LIGO-Virgo Public Alerts. arXiv (Cornell University). 8 indexed citations
16.
Edelman, B., B. Farr, Z. Doctor, et al.. (2021). Constraining unmodeled physics with compact binary mergers from GWTC-1. Physical review. D. 103(4). 15 indexed citations
17.
McIver, J., et al.. (2020). New methods to assess and improve LIGO detector duty cycle. Classical and Quantum Gravity. 37(17). 175008–175008. 8 indexed citations
18.
Farr, Will M., et al.. (2019). Detecting Supermassive Black Hole-induced Binary Eccentricity Oscillations with LISA. Repository of the Academy's Library (Library of the Hungarian Academy of Sciences). 55 indexed citations
19.
Nuttall, L. K., T. J. Massinger, J. S. Areeda, et al.. (2015). Improving the data quality of Advanced LIGO based on early engineering run results. Classical and Quantum Gravity. 32(24). 245005–245005. 41 indexed citations
20.
McIver, J., et al.. (2007). Wrinkling of a bilayer membrane. Physical Review E. 75(1). 16609–16609. 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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