
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. From 2023, I am Chair of the Astrostatistics Interest Group of the American Statistical Association. 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
The DEHVILS survey overview and initial data release: high-quality near-infrared Type Ia supernova light curves at low redshift
– Monthly Notices of the Royal Astronomical Society
(2023)
522,
2478
(doi: 10.1093/mnras/stad1077)
The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves
and Photometric Classification of 1975 Supernovae
(2022)
Constraining the SN Ia host galaxy dust law distribution and mass step: hierarchical BAYESN analysis of optical and near-infrared light curves
– Monthly Notices of the Royal Astronomical Society
(2022)
517,
2360
(doi: 10.1093/mnras/stac2714)
Real-time detection of anomalies in large-scale transient surveys
– Monthly Notices of the Royal Astronomical Society
(2022)
517,
393
(doi: 10.1093/mnras/stac2582)
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
– Astrophysical Journal
(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: 10.1088/1748-9326/ac7062)
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
– 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)
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