Christopher Lovell
Research Associate Cosmological Simulation Based Inference
London, England, United Kingdom
Summary
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RockstarChristopher Lovell is a research scientist specializing in cosmological simulation-based inference, combining 13 years of quantitative experience with machine learning to extract physical insights from high-redshift numerical simulations. Currently a Research Associate at the University of Cambridge after postdoctoral positions across UK institutions and a JSPS fellowship in Japan, he blends rigorous academic research with practical data-science skills honed earlier as a data scientist at the Bank of England. His work sits at the intersection of astrophysics and ML, translating complex simulation outputs into probabilistic constraints on cosmology. Colleagues appreciate that he moves fluidly between coding, statistical modeling, and large-scale simulation orchestration, often bringing techniques from industry data science into academic workflows.
12 years of coding experience
1 year of employment as a software developer
Stackoverflow
3,959reputation
294kreached
20answers
11questions
tmux
top-5%
ssh
top-5%
python
top-5%
dynamic
top-5%
jupyter
top-1%
Github Skills (132)
synthetic10
synthetic-data10
jupyter10
astrophysics10
pipeline9
python9
generative9
ssh9
dynamic9
eagle9
tmux9
science8
statistics8
qt8
bayesian-methods8
Programming languages (11)
Github contributions (5)
christopherlovell/sph2sed
Feb 2018 - Nov 2020
SED modelling for SPH simulations
Contributions:4 PRs, 55 pushes, 3 branches in 2 years 9 months
sedagent-based-modelingsph-simulationssimulationssimulation
christopherlovell/astro-python
Apr 2016 - Jan 2019
Practical notebooks introducing popular python modules for Astronomy
Contributions:29 commits, 2 PRs, 21 pushes in 2 years 9 months
astrologypythonpython-modulespracticalnotebooks
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