Jaime Ruiz Zapatero

Research Software Engineer

I am a research software engineer at the Advanced Research Computing (ARC) centre of University College London (UCL) developing infrastructure for the LSST and Euclid cosmological surveys to enable new science. I also have a deep interest in accelerating Bayesian inference with gradient methods and Gaussian processes as tools for model-agnostic science.

Expertise

Classical machine learning: developed tests of fundamental assumptions of modern Cosmology using Gaussian processes as tools for agnostic modelling.
High-dimensional statistical inference: developed gradient based inference algorithms to constrain thousands of parameters.
Big data reduction: co-author of the largest repository of consistently combined summary statistics in Cosmology from pixel maps.
Auto-differentiable programming: developed the first library of auto-differentiable methods for cosmology in Julia.

Projects

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MicroCanonicalHMC.jl

Gradient based sampler that uses one single energy level to explore large parameter spaces following Hamiltonian trajectories.

LimberJack.jl

Fully differentiable Julia code to compute predictions of summary statistics of cosmological observables.

Cosmoteka.py

Biggest repository of summary statistics combined in a statistically consistent way in Cosmology using Python

Education

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Astrophysics PhD at the University of Oxford (2020-2024)

• Supervisors: David Alonso & Pedro Ferreira

Long term attachment at the BCCP, UC Berkeley (Jan-May 2023)

• Supervisor: Uroš Seljak

Msci Theoretical Physics at UCL (2016-2020)

• Supervisor: Benjamin Joachimi

Bachillerato cientifico-tecnologico at La Salle Buen Pastor (2014-2016)

Honours

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• 2020 - STFC studentship

• 2020 - St Cross college studentship

• 2020 - UCL MAPS faculty Dean’s list

• 2020 - UCL MAPS faculty additional seasonal prize of merit

• 2016 - Premio extraordinario de bachillerato

• 2016 - Matricula de honor de Bachillerato

Work Experience

Research Software Engineer for LSST and Euclid at UCL, London (UK), Current

Euclid: building summary statistics from pixel maps.
LSST: speeding photometric uncertainty marginalisation.

Probabilistic programming engineer at the CBL Lab, Cambridge (UK), June-July 2023

Refactored the Turing.jl library for Bayesian inference from a monolithic into a microservice design by writing a new interface between Turing.jl's probabilistic programming language and external inference algorithms.

Natural language processing internship at Satalia (UK), Aug-Sept 2019

Developed a natural language processor to classify employees reports into the company's projects as well as a scheduler to asses and minimize project delays based on Monte Carlo simulations.

Teaching and other Responsibilities

Referee for OJA, EPJ-C, JCAP and APJ, free lance
Special Relativity and Symmetries tutor at St Peter's college, Oxford (2022)
BIPAC Cosmology journal club chair (2020-2022)
Leveling up physics mentor, Oxford (2021)