Andre Vauvelle is a quantitative researcher with eight years of experience at the intersection of machine learning, healthcare and quantitative finance, currently pursuing a PhD in Machine Learning for Healthcare at UCL funded by BenevolentAI. He has applied neural-network research and quantitative methods across industry roles from BlackRock’s FIGA research team to energy analytics at Dexter Energy and now Alipes ApS. His background blends rigorous engineering training (MEng, Oxford) with practical data-science internships in public health and pharma-focused AI, giving him a rare ability to translate complex models into domain-relevant solutions. Colleagues describe him as comfortable in “quandaries” — drawn to ambiguous problems where probabilistic thinking and experimentation pay off. Based in London with ties to Denmark, he combines academic depth with hands-on product-facing research.
8 years of coding experience
4 years of employment as a software developer
Master of Engineering (MEng), Engineering Science, Master of Engineering (MEng), Engineering Science at University of Oxford
Contributions:5 commits, 2 pushes in 1 year 11 months
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