skip to content
Home

Statistical Laboratory

Professor Kaisey Mandel

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 the Past Chair of the Astrostatistics Interest Group of the American Statistical Association, a member of the Council of the International Astrostatistics Association, and Turing Fellow Alumnus of The Alan Turing Institute. I am a founder and co-organiser of the Cambridge Astro Data Science Discussion Group. My research interests lie at the intersections of astrophysics, cosmology, statistics, and machine learning, and include:

  • Astrostatistics, astronomical machine learning, astroinformatics
  • Statistical applications in time-domain astronomy and cosmology
  • Bayesian modelling and inference
  • Statistical computation

Publications

Characterising the Standardisation Properties of Type Ia Supernovae in the z band with Hierarchical Bayesian Modelling
EE Hayes, S Dhawan, KS Mandel, DO Jones, RJ Foley, S Thorp, M Grayling, SM Ward, A Do, D Langeroodi, N Earl, KM de Soto, G Narayan, K Auchettl, T de Boer, KC Chambers, DA Coulter, C Gall, H Gao, L Izzo, C-C Lin, EA Magnier, A Rest, Q Wang
– Monthly Notices of the Royal Astronomical Society
(2025)
(doi: 10.1093/mnras/staf1056)
DAmodel: hierarchical Bayesian modelling of DA white dwarfs for spectrophotometric calibration
BM Boyd, G Narayan, KS Mandel, M Grayling, A Saha, T Axelrod, T Matheson, EW Olszewski, A Calamida, A Do, RC Bohlin, JB Holberg, I Hubeny, S Deustua, A Rest, CW Stubbs, A Berres, M Li, JW Mackenty, E Sabbi
– Monthly Notices of the Royal Astronomical Society
(2025)
540,
staf629
(doi: 10.1093/mnras/staf629)
The Multimodal Universe: 100 TB of Machine Learning Ready Astronomical Data
E Angeloudi, J Audenaert, M Bowles, BM Boyd, D Chemaly, B Cherinka, I Ciucă, M Cranmer, A Do, M Grayling, EE Hayes, T Hehir, S Ho, M Huertas-Company, KG Iyer, M Jablonska, F Lanusse, HW Leung, K Mandel, JR Martínez-Galarza, P Melchior, L Meyer, LH Parker, H Qu, J Shen, MJ Smith, M Walmsley, JF Wu
– Research Notes of the AAS
(2024)
8,
301
(doi: 10.3847/2515-5172/ad9a63)
Six Maxims of Statistical Acumen for Astronomical Data Analysis
H Tak, Y Chen, VL Kashyap, KS Mandel, XL Meng, A Siemiginowska, DA van Dyk
– The Astrophysical Journal Supplement Series
(2024)
275,
30
(doi: 10.3847/1538-4365/ad8440)
Hawaií Supernova Flows: A peculiar velocity survey using over a Thousand Supernovae in the near-infrared
A Do, BJ Shappee, JL Tonry, RB Tully, T de Jaeger, D Rubin, C Ashall, CR Burns, DD Desai, JT Hinkle, WB Hoogendam, ME Huber, DO Jones, KS Mandel, AV Payne, ER Peterson, D Scolnic, MA Tucker
– Monthly Notices of the Royal Astronomical Society
(2024)
536,
624
(doi: 10.1093/mnras/stae2501)
Variational inference for acceleration of SN Ia photometric distance estimation with BayeSN
ASM Uzsoy, S Thorp, M Grayling, KS Mandel
– Monthly Notices of the Royal Astronomical Society
(2024)
535,
2306
(doi: 10.1093/mnras/stae2465)
Quantifying interstellar extinction at high Galactic latitudes
M O’Callaghan, G Gilmore, KS Mandel
– Monthly Notices of the Royal Astronomical Society
(2024)
535,
stae2397
(doi: 10.1093/mnras/stae2397)
Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
PD Aleo, AW Engel, G Narayan, CR Angus, K Malanchev, K Auchettl, VF Baldassare, A Berres, TJL de Boer, BM Boyd, KC Chambers, KW Davis, N Esquivel, D Farias, RJ Foley, A Gagliano, C Gall, H Gao, S Gomez, M Grayling, DO Jones, CC Lin, EA Magnier, KS Mandel, T Matheson, SI Raimundo, VG Shah, MD Soraisam, KM de Soto, S Vicencio, VA Villar, RJ Wainscoat
– Astrophysical Journal
(2024)
974,
172
(doi: 10.3847/1538-4357/ad6869)
Scalable hierarchical BayeSN inference: investigating dependence of SN Ia host galaxy dust properties on stellar mass and redshift
M Grayling, S Thorp, KS Mandel, S Dhawan, ASM Uzsoy, BM Boyd, EE Hayes, SM Ward
– Monthly Notices of the Royal Astronomical Society
(2024)
531,
953
(doi: 10.1093/mnras/stae1202)
gausSN: Bayesian time-delay estimation for strongly lensed supernovae
EE Hayes, S Thorp, KS Mandel, N Arendse, M Grayling, S Dhawan
– Monthly Notices of the Royal Astronomical Society
(2024)
530,
3942
(doi: 10.1093/mnras/stae1086)
  • 1 of 8
  • >

Frontpage talks

There are no upcoming talks currently scheduled in this series.

Research Group

Statistical Laboratory

Email

kmandel@statslab.cam.ac.uk

Room

D1.07

Telephone

01223 337955

Personal homepage

https://www.dpmms.cam.ac.uk/~km723

    Study at Cambridge

    About the University

    Research at Cambridge