Phil Marshall

Senior Staff Scientist, SLAC
(650) 926-4682
Faculty Research Interests
Observational Cosmology

Phil's research interests are in observational cosmology using gravitational lensing: weighing galaxies, and measuring the expansion rate of the Universe. He is a member of the H0LiCOW and STRIDES collaborations, modeling time delay lenses in order to measure the Hubble constant, and is active in the LSST DESC Strong Lensing working group, helping design and implement its strong lensing science analysis. LSST presents astronomers with a new scale of Big Data problems, the solutions to which will necessarily involve either innovations in automated inference, or large numbers of people, or both: Phil's research is focused on strong lensing, but the methods he is investigating with the KIPAC students and postdocs have much wider applicability.

Phil did his PhD on Bayesian Analysis of Clusters of Galaxies at the University of Cambridge, in which he first got interested in the process of measuring astronomical objects, including things like Dark Matter halos which we may not be able to observe directly. He first moved to Stanford in 2003 as one of KIPAC's first wave of postdocs, and returned as Kavli Fellow in 2009 after three years as TABASGO Fellow at the University of California, Santa Barbara. Phil then spent three years in Oxford as a Royal Society University Research Fellow, before moving back to join the SLAC staff on a permanent basis in 2013. He is currently Deputy Director of Operations for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), thinking about how to set up the Rubin Observatory and its survey to successfully deliver the data products needed by, for example, the cosmology analysis planned by the LSST Dark Energy Science Collaboration (DESC). He helped form the LSST DESC at its inaugural meeting in 2012, and has held leadership positions in it ever since. Phil was LSST DESC Spokesperson in 2017-2019, during which time he led the implementation of the collaboration's operations plan.