Tom Loredo's research combines statistical data analysis with astrophysical theory to rigorously test astronomical models and theories, particularly in the areas of high energy astrophysics (supernovae, gamma-ray bursts, black holes, neutron stars) and cosmology. His work focuses on problems that can benefit from development of new statistical methodology, and largely adopts the Bayesian approach to statistics, an approach first developed by the French physicist Laplace but largely abandoned until recently. He also uses the conventional "frequentist" approach, and is particularly interested in problems where these two statistical approaches produce different results. Recently Tom's work has also addressed statistical issues arising in the study of extrasolar planets and analysis of the distribution of trans-Neptunian objects (including Kuiper belt objects).
Tom has been the principal investigator for a NASA-sponsored project developing a statistical inference package using the Python computing language. He is also a member of the Extrasolar Planet Interferometric Survey (EPIcS) team that will use NASA's Space Interferometry Mission to search for Earth-like planets around nearby stars and to take a census of planetary systems in the Solar neighborhood in all their diversity.