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Vahid Asadi

Observed name: V. Asadi
ORCID: 0009-0005-8897-2385
Observed ORCID: 0009-0005-8897-2385
OpenAlex ID: A5134718055
Leveraging Machine Learning for Accurate and Fast Stellar Mass Estimation of Galaxies
2025 · Vahid Asadi, Akram Hasani Zonoozi, et al. · The Astrophysical Journal · 8
Machine Learning Classification of COSMOS2020 Galaxies: Quiescent versus Star-forming
2025 · Vahid Asadi, Nima Chartab, et al. · The Astrophysical Journal · 6
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Semi-supervised classification of stars, galaxies and quasars using K-means and random-forest approaches
2025 · V. Asadi, H. Haghi, et al. · Astronomy and Astrophysics · 5
COSMOS2025: Machine Learning Classification of Early- and Late-type Galaxies at 0 < z < 3
2026 · Vahid Asadi, Najmeh Sheikhi · The Astrophysical Journal · 3
Machine Learning versus Spectral Energy Distribution Fitting: A Comparative Analysis of Accuracy in Stellar Mass Estimation
2026 · Vahid Asadi, Akram Hasani Zonoozi, et al. · The Astrophysical Journal · 3
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COSMOS2025: A Machine Learning Census of Massive Quiescent Galaxies at 2.5 < z < 5
2026 · Vahid Asadi, Hosein Haghi, et al. · The Astrophysical Journal
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Data for "COSMOS2025: Machine Learning Classification of Early- and Late-type Galaxies at 0< z <3"
2026 · Vahid Asadi · Zenodo (CERN European Organization for Nuclear Research)
ِِData for "Semi-supervised classification of stars, galaxies and quasars using K-means and random-forest approaches"
2026 · Vahid Asadi · Zenodo (CERN European Organization for Nuclear Research)
Data for "Machine Learning Classification of COSMOS2020 Galaxies: Quiescent versus Starforming"
2026 · Vahid Asadi · Zenodo (CERN European Organization for Nuclear Research)
catboost versus spectral energy distribution-fitting: estimating galaxy properties under controlled photometric incompleteness
2026 · Vahid Asadi, Hosein Haghi, et al. · Monthly Notices of the Royal Astronomical Society
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Data for " COSMOS2025: A Machine Learning Census of Massive Quiescent Galaxies at 2.5 < z < 5 "
2026 · Vahid Asadi, Haghi, Hosein, et al. · Zenodo (CERN European Organization for Nuclear Research)
A stable, label-efficient classifier for AGN/SFG separation in the MIGHTEE-COSMOS field
2026 · Vahid Asadi · SSRN Electronic Journal
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Works count: 12
Citation count: 25
H-index: 3
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