Scholar
Deaglan J. Bartlett
Google Scholar ID: wTj4UjSjpBkC
University of Oxford
Citations & Impact
Citations
476
H-index
12
i10-index
16
Publications
20
Co-authors
30
list available
Publications
Resume (English only)
Academic Achievements
- DPhil research focused on using the morphology and kinematics of galaxies to learn about galaxy formation and to constrain new Physics (theories beyond the standard models of cosmology (ΛCDM) and particle physics (SM)); Holds multiple research fellowships.
Research Experience
- Eric and Wendy Schmidt AI in Science Postdoctoral Fellow in the Department of Physics at The University of Oxford, working on projects at the border of artificial intelligence and Bayesian inference problems, within the framework of applications to cosmology; International Astronomical Union (IAU) The Gruber Foundation (TGF) Fellowship in Astrophysics for 2025/26; Nicholas Kurti Junior Research Fellowship at Brasenose College, Oxford for 2025-2028; Previously a Postdoctoral Fellow at the Institut d’Astrophysique de Paris, supported by the Simons Foundation on Learning the Universe, and co-leads the Accelerated Forward Modelling working group.
Education
- DPhil in Astrophysics, Oriel College, University of Oxford, supervised by Prof. Pedro Ferreira and Dr Harry Desmond; MA and MSci in Natural Sciences, Trinity College, University of Cambridge, Part III (Masters) Project supervised by Dr Will Handley.
Background
- Interested in statistical and machine learning methodology in astrophysics and cosmology, Bayesian large-scale structure inference, field-level inference, and probing dark energy and constraining dark matter with astronomical surveys. Also works on accelerating cosmological simulations using machine learning methods and methodological improvements and applications of symbolic regression, a machine-learning technique which directly learns analytic laws from data.
