Alexis Bellot
Research Scientist at Google DeepMind
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolAlexis Bellot is a research scientist at Google DeepMind with nine years of experience building AI that explains and predicts the effects of interventions, combining expertise in causality, fairness, and time-series modeling. He previously conducted postdoctoral research at Columbia under Elias Bareinboim, advancing causal inference, discovery, and transportability theory, and holds advanced degrees from Cambridge, Oxford, and Imperial College London. At DeepMind he focuses on AI safety and alignment, particularly understanding and mitigating risks from increasing agentic capabilities. Alexis blends rigorous theoretical work with practical concerns for deployment in high-dimensional, real-world settings, and maintains a public research portfolio detailing his models and methods.
9 years of coding experience
1 year of employment as a software developer
Master’s Degree, Applied Statistics, Master’s Degree, Applied Statistics at University of OxfordDoctor of Philosophy - PhD, ENGINEERING, Doctor of Philosophy - PhD, ENGINEERING at University of CambridgeBachelor’s Degree, Mathematics, Bachelor’s Degree, Mathematics at Imperial College London
French, Spanish, luxembourgeois, German, English
Github Skills (12)
generative8
ode-model6
synthetic6
testing5
ode5
deep-learning4
pytorch4
time-series3
machine-learning3
bayesian1
hierarchical1
survival1
Programming languages (3)
Github contributions (5)
alexisbellot/GCIT
Aug 2019 - Nov 2019
Conditional Independence Testing with Generative Adversarial Networks
Contributions:32 commits, 19 pushes, 1 comment in 3 months
pytorchdeep-learningadversarialconditionaltesting
alexisbellot/Graphical-modelling-continuous-time
Feb 2021 - Mar 2022
Graphical modelling with time series data using an ODE model
Contributions:16 commits, 1 PR, 2 pushes in 1 year 1 month
time-series-analysisode-modelseries-datagraphicaltime-series
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