Shivam Pandey

5.2k total citations
19 papers, 193 citations indexed

About

Shivam Pandey is a scholar working on Astronomy and Astrophysics, Instrumentation and Artificial Intelligence. According to data from OpenAlex, Shivam Pandey has authored 19 papers receiving a total of 193 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Astronomy and Astrophysics, 6 papers in Instrumentation and 4 papers in Artificial Intelligence. Recurrent topics in Shivam Pandey's work include Galaxies: Formation, Evolution, Phenomena (15 papers), Cosmology and Gravitation Theories (8 papers) and Astronomy and Astrophysical Research (6 papers). Shivam Pandey is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (15 papers), Cosmology and Gravitation Theories (8 papers) and Astronomy and Astrophysical Research (6 papers). Shivam Pandey collaborates with scholars based in United States, United Kingdom and France. Shivam Pandey's co-authors include Eric J. Baxter, Daniel Anglés‐Alcázar, Francisco Villaescusa-Navarro, J. Colin Hill, Shy Genel, Lars Hernquist, Tiziana Di Matteo, Bhuvnesh Jain, Yueying Ni and Marco Raveri and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Shivam Pandey

18 papers receiving 166 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shivam Pandey United States 10 158 58 38 29 20 19 193
Mischa Knabenhans Switzerland 5 221 1.4× 93 1.6× 49 1.3× 17 0.6× 20 1.0× 6 233
Albert Izard Spain 3 98 0.6× 31 0.5× 31 0.8× 11 0.4× 13 0.7× 3 106
Camila P. Novaes Brazil 11 243 1.5× 89 1.5× 27 0.7× 15 0.5× 19 0.9× 17 261
Alex I. Malz United States 9 124 0.8× 30 0.5× 50 1.3× 15 0.5× 6 0.3× 23 161
S. Fromenteau Mexico 7 157 1.0× 32 0.6× 41 1.1× 13 0.4× 17 0.8× 9 170
Felipe Avila Brazil 9 216 1.4× 77 1.3× 29 0.8× 9 0.3× 15 0.8× 20 221
Bill S. Wright United Kingdom 6 234 1.5× 111 1.9× 22 0.6× 12 0.4× 14 0.7× 6 250
Gabriela A. Marques United States 8 125 0.8× 35 0.6× 18 0.5× 11 0.4× 17 0.8× 12 134
L Whiteway United Kingdom 5 122 0.8× 80 1.4× 18 0.5× 9 0.3× 10 0.5× 8 156
S. Àvila Spain 7 146 0.9× 30 0.5× 60 1.6× 14 0.5× 11 0.6× 15 154

Countries citing papers authored by Shivam Pandey

Since Specialization
Citations

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

Fields of papers citing papers by Shivam Pandey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shivam Pandey

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

All Works

19 of 19 papers shown
1.
Pandey, Shivam, Jaime Salcido, C. To, et al.. (2025). Accurate connected modeling of gas thermodynamics and matter distribution. Physical review. D. 111(4). 3 indexed citations
2.
Bartlett, Deaglan J., et al.. (2025). SYREN-NEW: Precise formulae for the linear and nonlinear matter power spectra with massive neutrinos and dynamical dark energy. Astronomy and Astrophysics. 698. A1–A1. 4 indexed citations
3.
Pandey, Shivam, C. Sánchez, & Bhuvnesh Jain. (2025). Cosmology with imaging galaxy surveys: The impact of evolving galaxy bias and magnification. Physical review. D. 111(2). 1 indexed citations
4.
Pandey, Shivam. (2025). TranslaPdf: Pdf Translator Tool. INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT. 9(4). 1–9.
5.
Modi, Chirag, et al.. (2024). Sensitivity analysis of simulation-based inference for galaxy clustering. Monthly Notices of the Royal Astronomical Society. 536(1). 254–265. 9 indexed citations
6.
Baxter, Eric J. & Shivam Pandey. (2024). Inferring galaxy cluster masses from cosmic microwave background lensing with neural simulation based inference. Journal of Cosmology and Astroparticle Physics. 2024(9). 2–2. 1 indexed citations
7.
Genel, Shy, B. D. Wandelt, Shivam Pandey, et al.. (2024). Zooming by in the CARPoolGP Lane: New CAMELS-TNG Simulations of Zoomed-in Massive Halos. The Astrophysical Journal. 968(1). 11–11. 9 indexed citations
8.
To, C., et al.. (2024). Deciphering baryonic feedback with galaxy clusters. Journal of Cosmology and Astroparticle Physics. 2024(7). 37–37. 10 indexed citations
9.
Bolliet, Boris, Aleksandra Kusiak, Fiona McCarthy, et al.. (2024). class_sz I: Overview. SHILAP Revista de lepidopterología. 293. 8–8. 6 indexed citations
10.
Bartlett, Deaglan J., Carolina Cuesta-Lazaro, Pablo Lemos, et al.. (2024). LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology. SHILAP Revista de lepidopterología. 7. 16 indexed citations
11.
Ni, Yueying, Shy Genel, Daniel Anglés‐Alcázar, et al.. (2023). The CAMELS Project: Expanding the Galaxy Formation Model Space with New ASTRID and 28-parameter TNG and SIMBA Suites. The Astrophysical Journal. 959(2). 136–136. 33 indexed citations
12.
Wadekar, Digvijay, Leander Thiele, J. Colin Hill, et al.. (2023). The SZ flux-mass (Y–M) relation at low-halo masses: improvements with symbolic regression and strong constraints on baryonic feedback. Monthly Notices of the Royal Astronomical Society. 522(2). 2628–2643. 22 indexed citations
13.
Anglés‐Alcázar, Daniel, Leander Thiele, Shivam Pandey, et al.. (2023). Predicting the impact of feedback on matter clustering with machine learning in CAMELS. Monthly Notices of the Royal Astronomical Society. 526(4). 5306–5325. 18 indexed citations
14.
Baxter, Eric J., Shivam Pandey, Susmita Adhikari, et al.. (2023). The impact of halo concentration on the Sunyaev Zel’dovich effect signal from massive galaxy clusters. Monthly Notices of the Royal Astronomical Society. 527(3). 7847–7860. 1 indexed citations
15.
Pandey, Shivam, Eric J. Baxter, Yueying Ni, et al.. (2023). Inferring the impact of feedback on the matter distribution using the Sunyaev Zel’dovich effect: insights from CAMELS simulations and ACT + DES data. Monthly Notices of the Royal Astronomical Society. 525(2). 1779–1794. 23 indexed citations
16.
17.
Baxter, Eric J., Martin G. Haehnelt, Vid Iršič, et al.. (2021). The correlation of high-redshift galaxies with the thermal Sunyaev–Zel’dovich effect traces reionization. Monthly Notices of the Royal Astronomical Society. 501(4). 6215–6224. 4 indexed citations
18.
Pandey, Shivam, Marco Raveri, & Bhuvnesh Jain. (2020). Model independent comparison of supernova and strong lensing cosmography: Implications for the Hubble constant tension. Physical review. D. 102(2). 12 indexed citations
19.
Pandey, Shivam, Eric J. Baxter, & J. Colin Hill. (2020). Constraining the properties of gaseous halos via cross-correlations of upcoming galaxy surveys and thermal Sunyaev-Zel’dovich maps. Physical review. D. 101(4). 16 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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