Rahul Shah

About

I am a Senior Research Fellow (Ph.D. Student) at the Indian Statistical Institute in Kolkata, India.

My current research interests lie broadly in Cosmology, with a side of High-Energy Physics and Astro-Particle Physics, with my current focus being on the persistent Tensions and Anomalies in Cosmology.

I am heavily passionate about computation and the application of all sorts of cutting-edge developments in computer science and statistics to the study of the cosmos and our very existence.

Employment

• Indian Statistical Institute Ph. D. (Senior Research Fellow)
  2022 - Present
• Indian Statistical Institute Ph. D. (Junior Research Fellow)
  2020 - 2022
• Indian Association for the Cultivation of Science Graduate Student (M. Sc.)
  2018 - 2020

Education

• Indian Statistical Institute Ph. D. Student
  2020 - Present
• Indian Association for the Cultivation of Science Master of Science (M. Sc.)
  2018 - 2020
• St. Xavier's College Bachelor of Science (B. Sc.)
  2015 - 2018

Projects & Funding

Projects & funding information is unavailable.

Publications (12)

• Probing interacting dark sectors with upcoming post-reionization and galaxy surveys
  Mon.Not.Roy.Astron.Soc. 2026 DOI: 10.1093/mnras/stag1124
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• Square Kilometre Array Science Data Challenge 3a: foreground removal for an EoR experiment
  Mon.Not.Roy.Astron.Soc. 2025 DOI: 10.1093/mnras/staf1466
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• Interacting dark sectors in light of DESI DR2
  Mon.Not.Roy.Astron.Soc. 2025 DOI: 10.1093/mnras/staf1442
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• The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics
  Phys.Dark Univ. 2025 DOI: 10.1016/j.dark.2025.101965
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• Reconciling S8: insights from interacting dark sectors
  Mon.Not.Roy.Astron.Soc. 2024 DOI: 10.1093/mnras/stae2712
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• LADDER: Revisiting the Cosmic Distance Ladder with Deep Learning Approaches and Exploring Its Applications
  Astrophys.J.Suppl. 2024 DOI: 10.3847/1538-4365/ad5558
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• Role of future SNIa data from Rubin LSST in reinvestigating cosmological models
  Mon.Not.Roy.Astron.Soc. 2024 DOI: 10.1093/mnras/stae1016
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• LADDER - Revisiting the Cosmic Distance Ladder with Deep Learning Approaches and Exploring its Applications
  Zenodo 2024 DOI: 10.5281/zenodo.11175054
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• Reconstructing the Hubble Parameter with Future Gravitational-wave Missions Using Machine Learning
  Astrophys.J. 2023 DOI: 10.3847/1538-4357/ad055f
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• A thorough investigation of the prospects of eLISA in addressing the Hubble tension: Fisher forecast, MCMC and Machine Learning
  JCAP 2023 DOI: 10.1088/1475-7516/2023/06/038
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