Arya Farahi

5.8k total citations
46 papers, 611 citations indexed

About

Arya Farahi is a scholar working on Astronomy and Astrophysics, Instrumentation and Economics and Econometrics. According to data from OpenAlex, Arya Farahi has authored 46 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Astronomy and Astrophysics, 10 papers in Instrumentation and 5 papers in Economics and Econometrics. Recurrent topics in Arya Farahi's work include Galaxies: Formation, Evolution, Phenomena (23 papers), Astronomy and Astrophysical Research (10 papers) and Cosmology and Gravitation Theories (7 papers). Arya Farahi is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (23 papers), Astronomy and Astrophysical Research (10 papers) and Cosmology and Gravitation Theories (7 papers). Arya Farahi collaborates with scholars based in United States, United Kingdom and Germany. Arya Farahi's co-authors include A. E. Evrard, Andrew Benson, Junfeng Jiao, Dragan Huterer, Adrian Jenkins, Mark R. Lovell, Leonidas A. Moustakas, Carlos S. Frenk, Rachel Kennedy and John Helly and has published in prestigious journals such as Physical Review Letters, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Arya Farahi

36 papers receiving 578 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arya Farahi United States 16 481 186 181 54 39 46 611
D. Kirkby United States 11 297 0.6× 189 1.0× 66 0.4× 42 0.8× 29 0.7× 35 564
M. Prescott South Africa 14 553 1.1× 147 0.8× 249 1.4× 24 0.4× 16 0.4× 21 668
D. Gruen United States 15 482 1.0× 54 0.3× 216 1.2× 73 1.4× 37 0.9× 30 636
Björn Malte Schäfer Germany 14 830 1.7× 195 1.0× 300 1.7× 75 1.4× 22 0.6× 54 922
Cora Uhlemann France 15 551 1.1× 234 1.3× 95 0.5× 34 0.6× 30 0.8× 30 614
Shadab Alam United States 21 767 1.6× 233 1.3× 292 1.6× 23 0.4× 26 0.7× 38 814
C. M. Gutiérrez Spain 15 634 1.3× 186 1.0× 172 1.0× 44 0.8× 5 0.1× 47 731
Mitchell F. Struble United States 12 663 1.4× 119 0.6× 319 1.8× 18 0.3× 32 0.8× 37 725
R. Valdarnini Italy 14 585 1.2× 144 0.8× 173 1.0× 14 0.3× 16 0.4× 35 652
R. Domı́nguez-Tenreiro Spain 17 829 1.7× 160 0.9× 353 2.0× 13 0.2× 11 0.3× 69 884

Countries citing papers authored by Arya Farahi

Since Specialization
Citations

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

Fields of papers citing papers by Arya Farahi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arya Farahi

This figure shows the co-authorship network connecting the top 25 collaborators of Arya Farahi. A scholar is included among the top collaborators of Arya Farahi 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 Arya Farahi. Arya Farahi 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.
Combet, Céline, T. Guillemin, M. Ricci, et al.. (2025). Weak lensing mass-richness relation of redMaPPer clusters in LSST DESC DC2 simulations. Astronomy and Astrophysics. 700. A34–A34.
2.
Evrard, A. E., Arya Farahi, Annalisa Pillepich, et al.. (2025). Mass proxy quality of massive halo properties in the illustrisTNG and flamingo simulations: I. Hot gas. Monthly Notices of the Royal Astronomical Society. 544(1). 67–94.
3.
4.
Dao, Tien Tuan, Jennifer Williams, John Robert Bautista, et al.. (2025). TAME Pain data release: using audio signals to characterize pain. Scientific Data. 12(1). 595–595. 1 indexed citations
5.
Farahi, Arya & Junfeng Jiao. (2024). Analyzing racial disparities in the United States homeownership: A socio-demographic study using machine learning. Cities. 152. 105181–105181. 2 indexed citations
6.
7.
Farahi, Arya, Elvira Pérez Vallejos, Zoë S. Walters, et al.. (2024). Insights from explainable AI in oesophageal cancer team decisions. Computers in Biology and Medicine. 180. 108978–108978. 1 indexed citations
8.
Villaescusa-Navarro, Francisco, Paul Torrey, Arya Farahi, et al.. (2024). Can We Constrain Warm Dark Matter Masses with Individual Galaxies?. The Astrophysical Journal. 970(2). 170–170.
9.
Jiao, Junfeng, et al.. (2024). Fire and smoke digital twin – A computational framework for modeling fire incident outcomes. Computers Environment and Urban Systems. 110. 102093–102093. 11 indexed citations
10.
Farahi, Arya, Daisuke Nagai, Erwin T. Lau, et al.. (2024). Impact of property covariance on cluster weak lensing scaling relations. Monthly Notices of the Royal Astronomical Society. 530(3). 3127–3149. 1 indexed citations
11.
Aung, Han, et al.. (2023). C 2 -GaMe: Classification of cluster galaxy membership with machine learning. Astronomy and Computing. 45. 100743–100743. 4 indexed citations
12.
Williams, Jennifer, Arya Farahi, Tina Seabrooke, et al.. (2023). TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients. ePrints Soton (University of Southampton). 1–4. 2 indexed citations
13.
Farahi, Arya, et al.. (2023). Benchmarks and explanations for deep learning estimates of X-ray galaxy cluster masses. Monthly Notices of the Royal Astronomical Society. 524(3). 3289–3302. 8 indexed citations
14.
Wu, Hao‐Yi, M. Costanzi, C. To, et al.. (2022). Optical selection bias and projection effects in stacked galaxy cluster weak lensing. Monthly Notices of the Royal Astronomical Society. 515(3). 4471–4486. 23 indexed citations
15.
Ntampaka, Michelle, John F. Wu, John ZuHone, et al.. (2022). A Machine-learning Approach to Enhancing eROSITA Observations. The Astrophysical Journal. 940(1). 60–60. 4 indexed citations
16.
Anbajagane, Dhayaa, A. E. Evrard, & Arya Farahi. (2021). Baryonic imprints on DM haloes: population statistics from dwarf galaxies to galaxy clusters. Monthly Notices of the Royal Astronomical Society. 509(3). 3441–3461. 27 indexed citations
17.
Anbajagane, Dhayaa, A. E. Evrard, Arya Farahi, et al.. (2020). Stellar property statistics of massive haloes from cosmological hydrodynamics simulations: common kernel shapes. Monthly Notices of the Royal Astronomical Society. 495(1). 686–704. 22 indexed citations
18.
Farahi, Arya, A. E. Evrard, G. P. Smith, et al.. (2019). LoCuSS: scaling relations between galaxy cluster mass, gas, and stellar content. Monthly Notices of the Royal Astronomical Society. 484(1). 60–80. 35 indexed citations
19.
Pierre, M., Arya Farahi, A. E. Evrard, et al.. (2018). The cosmological analysis of X-ray cluster surveys. Astronomy and Astrophysics. 617. C2–C2. 1 indexed citations
20.
Pierre, M., Arya Farahi, A. E. Evrard, et al.. (2018). The cosmological analysis of X-ray cluster surveys. Astronomy and Astrophysics. 614. A72–A72. 3 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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