Gautham Narayan is the Lasker Fellow at STScI.
He works on understanding the properties of dark energy using surveys of type Ia supernovae. He is developing hierarchical Bayesian models to determine their luminosity distances, and infer cosmological parameters from large samples including Pan-STARRS, ESSENCE and the upcoming LSST. He tries to understand the physics of explosive transients with light curves from the K2 mission as part of the KEGS team. He is one of the lead developers on the ANTARES project, using machine learning techniques to classify variables and transients, and build a real-time alert broker for wide-field surveys. He is part of the LSST PLAsTiCC team, generating large simulations for a public classification challenge. He also works on photometric calibration and is involved in a large effort to establish the next generation of spectrophotometric standards using faint DA white dwarfs, extending the CALSPEC system to ground-based surveys. He Monte Carlos quite literally all of the things.
He recieved his PhD in Physics from Harvard University in May 2013, working with Christopher Stubbs and Robert Kirshner. Before moving to STScI, he was a postdoc at the National Optical Astronomy Observatory (NOAO) working with Abhijit Saha and Tom Matheson.
PhD in Physics, Harvard University, Cambridge, MA
BS in Physics, Illinois Wesleyan University, Bloomington, IL
- hierarchical Bayesian models for SNIa and WD
- cosmological inference with SNIa
- alert broker development and machine learning for classification of variables and transients
- photometric calibration of wide-field UVOIR surveys
Research Topics: Supernovae, Dark Energy, Cosmology, Wide-field synoptic surveys, Astrostatistics, Machine Learning, Photometry, Calibration
ORCID ID: 0000-0001-6022-0484