Arya Farahi

Assistant Professor

University of Texas at Austin

United States

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About

Arya Farahi is an Assistant Professor at The University of Texas at Austin. His research primarily focuses on astrophysics, particularly in weak lensing, dark matter, and machine learning applications. Recent publications include studies on galaxy clusters, cosmic simulations, and explainable AI in healthcare decision-making. He is actively engaged in advancing understanding in areas such as resource allocation inequalities and pain characterization through audio signals.

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Collaborators (24)

Camille Avestruz

Assistant Professor

University of Michigan

UNITED STATES

Arya Farahi

Research Interests

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About

Articles (25)

Baryon Pasting the Uchuu Light-cone Simulation

Weak lensing mass-richness relation of redMaPPer clusters in LSST DESC DC2 simulations

TAME Pain data release: using audio signals to characterize pain

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations

Insights from explainable AI in oesophageal cancer team decisions.

Can We Constrain Warm Dark Matter Masses with Individual Galaxies?

Measuring and Mitigating Group Inequalities In Resource Allocation

U-trustworthy Models. Reliability, Competence, and Confidence in Decision-Making

Copacabana: a probabilistic membership assignment method for galaxy clusters

Masses of Sunyaev-Zel’dovich galaxy clusters detected by the Atacama Cosmology Telescope: Stacked lensing measurements with Subaru HSC year 3 data

Dark Energy Survey Year 3 Results

Benchmarks and explanations for deep learning estimates of X-ray galaxy cluster masses

Dark Energy Survey Year 3 results: redshift calibration of the MagLim lens sample from the combination of SOMPZ and clustering and its impact on cosmology

C<sup>2</sup>-GAME: Classification of cluster galaxy membership with machine learning

Combatting the mismatch: Modeling bike-sharing rental and return machine learning classification forecast in Seoul, South Korea

Disparities in affecting factors of housing price: A machine learning approach to the effects of housing status, public transit, and density factors on single-family housing price

HSC-XXL: Baryon budget of the 136 XXL groups and clusters

Dark Energy Survey Year 3 Results

Galaxy velocity bias in cosmological simulations: towards per cent-level calibration

A Machine-learning Approach to Enhancing eROSITA Observations

Velocity dispersions of clusters in the Dark Energy Survey Y3 redMaPPer catalogue

Correlations of Dark Matter, Gas, and Stellar Profiles in Dark Matter Halos

KLLR: A Scale-dependent, Multivariate Model Class for Regression Analysis

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

Dark energy survey year 3 results: High-precision measurement and modeling of galaxy-galaxy lensing

Collaborators (24)

Camille Avestruz

Mikhail Medvedev

Xiao Fang

Jessica Muir

Seshadri Nadathur

Ken Osato

Santiago Avila

Elvira Perez Vallejos

Zoe Walters

Marcelle Soares-Santos

Daisuke Nagai

Martin Rodriguez-Monroy

Mariangela Lisanti

Pablo Lemos

Alexandra Amon

Vivian Miranda

Michelle Ntampaka

Marina Ricci

Gary Bernstein

Tim Underwood

Robert Gruendl

August Evrard

Nobuhiro Okabe

Elisabeth Krause

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