I am the Professor of Astrostatistics and Data Science at the University of Cambridge. I hold this interdisciplinary faculty position jointly at the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics, and at the Institute of Astronomy. As of 2024, I am Past Chair of the Astrostatistics Interest Group of the American Statistical Association and a Turing Fellow Alumnus of The Alan Turing Institute. My research interests lie at the intersections of astrophysics, cosmology, statistics, and machine learning.
Research Interests: Astrostatistics and astroinformatics, Applications in time-domain astronomy and cosmology, Bayesian modeling and inference, Statistical computation
Publications
Cosmological Results from the RAISIN Survey: Using Type Ia Supernovae in the Near Infrared as a Novel Path to Measure the Dark Energy Equation of State
– The Astrophysical Journal: an international review of astronomy and astronomical physics
(2022)
933,
172
(doi: 10.3847/1538-4357/ac755b)
Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference
– Environmental Research Letters
(2022)
17,
064037
(doi: 10.17863/CAM.85240)
Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference
– Environmental Research Letters
(2022)
(doi: 10.1088/1748-9326/ac7062)
An Early-time Optical and Ultraviolet Excess in the Type-Ic SN 2020oi
– The Astrophysical Journal
(2022)
924,
55
(doi: 10.3847/1538-4357/ac35ec)
A hierarchical Bayesian SED model for Type Ia supernovae in the optical to near-infrared
– Monthly Notices of the Royal Astronomical Society
(2021)
510,
3939
(doi: 10.1093/mnras/stab3496)
Testing the consistency of dust laws in SN Ia host galaxies: a BayeSN examination of Foundation DR1
– Monthly Notices of the Royal Astronomical Society
(2021)
508,
4310
(doi: 10.1093/mnras/stab2849)
Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)
(2020)
(doi: 10.48550/arxiv.2012.12392)
First cosmology results using supernovae ia from the dark energy survey: Survey overview, performance, and supernova spectroscopy
– The Astronomical Journal
(2020)
160,
267
(doi: 10.3847/1538-3881/abc01b)
Type Ia Supernovae are Excellent Standard Candles in the Near-Infrared
– The Astrophysical Journal
(2019)
887,
106
(doi: 10.3847/1538-4357/ab2a16)
The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC: Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals
– The Astronomical Journal
(2019)
158,
171
(doi: 10.3847/1538-3881/ab3a2f)
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