Observational Cosmologist
Tanveer Karim
Dunlap Postdoctoral Fellow at the University of Toronto
I map the largest structures in the Universe with next-generation galaxy surveys — and build the statistical and machine-learning methods that turn that data into physics.
Research at a glance
All research →
Galaxies × the Cosmic Microwave Background
Cross-correlating DESI's tens of millions of galaxies with maps of the cosmic microwave background to measure how structure grows — and to probe the σ₈ tension.
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The High-Redshift Universe with Lyman-Break Galaxies
Pushing cosmological analysis out to redshifts 2 < z < 5 with Lyman-Break Galaxies — and pinning down the systematics that stand in the way.
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Robust Inference & Machine Learning for Cosmology
Building the statistical and machine-learning machinery — model selection, emulators, systematics control — that decides what we can actually learn from cosmological data.
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The Milky Way & Early Research
From the Milky Way's giant γ-ray outflow to the rotation of newborn stars — Galactic and stellar astrophysics, including my earliest research.
Read more →Harvard
Ph.D. & A.M. in Astronomy
DESI
Builder · co-leads the Photo-z Topical Team
DESC
Co-leads the Lyman-Break Galaxies Topical Team
12+
Peer-reviewed publications
Selected publications
Full list →- 2025 Measuring σ₈ using DESI Legacy Imaging ELGs and Planck CMB lensing, and the impact of dust on parameter inference Journal of Cosmology and Astroparticle Physics (first author)
- 2023 On the impact of the galaxy window function on cosmological parameter estimation Monthly Notices of the Royal Astronomical Society (first author)
- 2022 Diverse metallicities of Fermi bubble clouds indicate dual origins in the disk and halo Nature Astronomy
- 2023 Target Selection and Validation of DESI Emission Line Galaxies The Astronomical Journal
About
I am an observational cosmologist who uses data from the largest galaxy surveys to test our models of the Universe. I am a builder of the Dark Energy Spectroscopic Instrument (DESI) and co-lead its Photo-z Topical Team, where I lead efforts to cross-correlate galaxy samples with external CMB datasets. I also co-lead the Lyman-Break Galaxies topical team within the Dark Energy Science Collaboration, constraining cosmology with the $2 < z < 5$ Universe.
I earned my Ph.D. and A.M. from the Department of Astronomy, Harvard University and my B.S. from the Department of Physics & Astronomy, University of Rochester. I was born and raised in Dhaka, Bangladesh before immigrating to New York.
I am increasingly excited about bringing machine learning and AI to cosmology — and about the bridge between theory and observation: how do we actually know we have learned something new about a model from data? Alongside research, I care deeply about mentoring and building a more inclusive astronomy. If any of this resonates, get in touch.