Kaisey Mandel

Kaisey Mandel serves as Professor of Astrostatistics and Data Science at the University of Cambridge with a joint appointment between the Statistical Laboratory of the Department of Pure Mathematics and Mathematical Statistics (Faculty of Mathematics) and the Institute of Astronomy. Her astronomy office is located at the Kavli Institute for Cosmology. As of 2024, she is Past Chair of the Astrostatistics Interest Group of the American Statistical Association, a member of the Council of the International Astrostatistics Association, and a Turing Fellow Alumnus of The Alan Turing Institute. She founded and co-organizes the Cambridge Astro Data Science Discussion Group.

• University: University of Cambridge
• School: Faculty of Mathematics
• Departments: Department of Pure Mathematics and Mathematical Statistics, Institute of Astronomy
• Office Location: Kavli Institute for Cosmology (Kavli K03)

Mandel's research focuses at the intersection of astrophysics, cosmology, statistics, and machine learning. Her primary research areas include supernova cosmology, astrostatistics, astronomical machine learning, astroinformatics, time-domain and transient astronomy, Bayesian modeling and inference, and statistical computation. She leads a research group that partners with the Young Supernova Experiment time-domain survey using Pan-STARRS telescopes and participates in LSST:UK, Time-Domain Extragalactic Survey (TiDES), International CHASC Astro-Statistics Collaboration, and MSCA-RISE ASTROSTAT-II Collaboration Network.

Her recent publications (2023-2025) demonstrate a strong focus on Bayesian hierarchical modeling applied to supernova cosmology, particularly addressing standardization of Type Ia supernovae, dust extinction properties, and cosmological parameter estimation. Her work increasingly incorporates machine learning techniques while maintaining rigorous statistical foundations. The publications span top astronomy journals including Monthly Notices of the Royal Astronomical Society and Astrophysical Journal.

• European Research Council Consolidator Grant (2020)
• ISBA Savage Award for Outstanding Doctoral Dissertation in Applied Statistical Methodology (2011)

Mandel has received significant research funding including an ERC Consolidator Grant and has mentored numerous students who have won awards in astrostatistics competitions. She teaches Astrostatistics courses for Part III Maths/Astrophysics students during Lent terms. Her research group actively collaborates with major astronomical surveys and has developed specialized statistical methodologies for time-domain astronomy.

She maintains active research laboratories within both the Statistical Laboratory and the Institute of Astronomy, facilitating interdisciplinary work that bridges astronomy and statistics. Her group develops computational tools for astronomical data analysis and contributes to major international collaborations focused on cosmological parameter estimation.