Tom Loredo

University of Chicago

Senior Research Associate & Lecturer

I’m an astrostatician who works mainly on cosmic demographics problems and time series problems across many subareas of astrophysics—minor planets (TNOs/KBOs), exoplanets, extragalactic astronomy, high-energy astrophysics (GRBs, X-ray pulsars, supernova neutrinos, UHE cosmic rays), and cosmology. I helped introduce modern Bayesian methods into astronomy in the late 1980s and 1990s, including the use of hierarchical Bayesian methods for cosmic demographics. My current work also involves Bayesian machine learning (focusing on accurate uncertainty quantification) and manifold learning (particularly in the context of photometric redshift estimation). I led the team that founded the ISSC in 2009 and co-chaired the ISSC from 2015-2022.

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