Jorge Martínez-Palomera

1.1k total citations
22 papers, 323 citations indexed

About

Jorge Martínez-Palomera is a scholar working on Astronomy and Astrophysics, Instrumentation and Computational Mechanics. According to data from OpenAlex, Jorge Martínez-Palomera has authored 22 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Astronomy and Astrophysics, 5 papers in Instrumentation and 3 papers in Computational Mechanics. Recurrent topics in Jorge Martínez-Palomera's work include Stellar, planetary, and galactic studies (14 papers), Gamma-ray bursts and supernovae (13 papers) and Galaxies: Formation, Evolution, Phenomena (6 papers). Jorge Martínez-Palomera is often cited by papers focused on Stellar, planetary, and galactic studies (14 papers), Gamma-ray bursts and supernovae (13 papers) and Galaxies: Formation, Evolution, Phenomena (6 papers). Jorge Martínez-Palomera collaborates with scholars based in United States, Chile and France. Jorge Martínez-Palomera's co-authors include Johan Richard, P. Lira, F. Förster, L. Wisotzki, R. Pelló, David Lagattuta, Guillaume Mahler, Vera Patrício, G. Soucail and B. Clément and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

Jorge Martínez-Palomera

19 papers receiving 304 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jorge Martínez-Palomera United States 10 312 114 53 38 18 22 323
Hyunjin Shim South Korea 12 358 1.1× 205 1.8× 43 0.8× 20 0.5× 23 1.3× 45 397
T. Emil Rivera-Thorsen Sweden 13 404 1.3× 143 1.3× 58 1.1× 23 0.6× 16 0.9× 24 427
Genoveva Micheva Germany 10 296 0.9× 108 0.9× 38 0.7× 16 0.4× 16 0.9× 25 309
Martin Eriksen Spain 11 205 0.7× 83 0.7× 31 0.6× 30 0.8× 13 0.7× 23 243
M. D. Gladders United States 9 346 1.1× 169 1.5× 67 1.3× 32 0.8× 15 0.8× 20 365
O. Streicher Germany 7 329 1.1× 155 1.4× 36 0.7× 43 1.1× 18 1.0× 21 370
A. Zenteno United States 9 367 1.2× 108 0.9× 89 1.7× 21 0.6× 11 0.6× 18 388
Jongwan Ko South Korea 13 310 1.0× 167 1.5× 48 0.9× 31 0.8× 9 0.5× 46 328
Annino Vaccarella Australia 4 264 0.8× 136 1.2× 33 0.6× 40 1.1× 13 0.7× 17 293
Hannah Stacey Germany 12 421 1.3× 137 1.2× 86 1.6× 40 1.1× 10 0.6× 26 446

Countries citing papers authored by Jorge Martínez-Palomera

Since Specialization
Citations

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

Fields of papers citing papers by Jorge Martínez-Palomera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge Martínez-Palomera. 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 Jorge Martínez-Palomera. The network helps show where Jorge Martínez-Palomera may publish in the future.

Co-authorship network of co-authors of Jorge Martínez-Palomera

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge Martínez-Palomera. A scholar is included among the top collaborators of Jorge Martínez-Palomera 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 Jorge Martínez-Palomera. Jorge Martínez-Palomera 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.
Martínez-Palomera, Jorge, et al.. (2025). A self-regulated convolutional neural network for classifying variable stars. Monthly Notices of the Royal Astronomical Society. 540(4). 3263–3280.
2.
Martínez-Palomera, Jorge, et al.. (2025). Prediscovery TESS Observations of Interstellar Object 3I/ATLAS. The Astrophysical Journal Letters. 994(2). L51–L51. 1 indexed citations
3.
Hedges, Christina, Jorge Martínez-Palomera, T. A. Pritchard, et al.. (2025). lkspacecraft: A Tool for Obtaining Orbital Properties of the Kepler and TESS Spacecraft. Research Notes of the AAS. 9(7). 186–186. 1 indexed citations
4.
Martínez-Palomera, Jorge, Christina Hedges, & Jessie Dotson. (2023). Kepler Bonus: Light Curves of Kepler Background Sources. The Astronomical Journal. 166(6). 265–265. 6 indexed citations
5.
Martínez-Palomera, Jorge, et al.. (2022). Deep Generative Modeling of Periodic Variable Stars Using Physical Parameters. The Astronomical Journal. 164(6). 263–263. 6 indexed citations
6.
Martínez-Palomera, Jorge, et al.. (2022). A Machine Learning Framework to Predict Images of Edge-on Protoplanetary Disks. The Astrophysical Journal. 939(2). 73–73. 2 indexed citations
7.
Martínez-Palomera, Jorge, Christina Hedges, Joseph E. Rodriguez, Geert Barentsen, & Jessie Dotson. (2022). Kepler Bonus: Aperture Photometry Light Curves of EXBA Sources. The Astronomical Journal. 163(2). 93–93. 3 indexed citations
8.
Hedges, Christina, Nicholas Saunders, & Jorge Martínez-Palomera. (2021). Contaminante: A Tool for Automatically Finding a Close-to-optimal Aperture for Transiting Signals in Kepler, K2, and TESS Data. Research Notes of the AAS. 5(11). 260–260. 2 indexed citations
9.
Stahl, Benjamin E., Jorge Martínez-Palomera, WeiKang Zheng, et al.. (2020). deepSIP: linking Type Ia supernova spectra to photometric quantities with deep learning. Monthly Notices of the Royal Astronomical Society. 496(3). 3553–3571. 8 indexed citations
10.
Peña, José Martínez, César Fuentes, F. Förster, et al.. (2020). Asteroids’ Size Distribution and Colors from HITS. The Astronomical Journal. 159(4). 148–148. 9 indexed citations
11.
Martínez-Palomera, Jorge, et al.. (2020). Introducing the Search for Intermediate-mass Black Holes in Nearby Galaxies (SIBLING) Survey. The Astrophysical Journal. 889(2). 113–113. 18 indexed citations
12.
Bloom, J. S., Catherine Zucker, Douglas P. Finkbeiner, et al.. (2019). LIGO/Virgo S190425z: DECam Observations of the UVOT Candidate Region.. GRB Coordinates Network. 24337. 1.
13.
Medina, G. E., Ricardo R. Muñoz, A. K. Vivas, et al.. (2018). Discovery of Distant RR Lyrae Stars in the Milky Way Using DECam. The Astrophysical Journal. 855(1). 43–43. 26 indexed citations
14.
Patrício, Vera, Johan Richard, David Carton, et al.. (2018). Kinematics, turbulence, and star formation of z ∼ 1 strongly lensed galaxies seen with MUSE. Monthly Notices of the Royal Astronomical Society. 477(1). 18–44. 24 indexed citations
15.
Peña, José Martínez, César Fuentes, F. Förster, et al.. (2018). Asteroids in the High Cadence Transient Survey. The Astronomical Journal. 155(3). 135–135. 4 indexed citations
16.
Lira, P., S. Kaspi, H. Netzer, et al.. (2018). Reverberation Mapping of Luminous Quasars at High z. The Astrophysical Journal. 865(1). 56–56. 49 indexed citations
17.
Medina, G. E., Ricardo R. Muñoz, A. K. Vivas, et al.. (2017). Serendipitous Discovery of RR Lyrae Stars in the Leo V Ultra-faint Galaxy. The Astrophysical Journal Letters. 845(1). L10–L10. 12 indexed citations
18.
Mahler, Guillaume, Johan Richard, B. Clément, et al.. (2017). Strong-lensing analysis of A2744 with MUSE and Hubble Frontier Fields images. Monthly Notices of the Royal Astronomical Society. 473(1). 663–692. 87 indexed citations
19.
Paraficz, D., Jean‐Paul Kneib, Johan Richard, et al.. (2016). The Bullet cluster at its best: weighing stars, gas, and dark matter. Astronomy and Astrophysics. 594. A121–A121. 24 indexed citations
20.
Martínez-Palomera, Jorge, et al.. (1998). Digitally recorded lightning impulse with overshoot parameter evaluation by using the Kalman filtering method. IEEE Transactions on Power Delivery. 13(4). 1005–1014. 14 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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