Felix Biggs
Applied Scientist at Wayve
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolFelix Biggs is an applied scientist with nine years of experience translating foundational ML theory into practical, safety-minded AI systems. He completed a PhD at UCL that produced six first-author papers (including a NeurIPS Spotlight) proving novel, non-vacuous generalisation guarantees and proposing algorithms that reduce the need for conventional test-set validation. Felix has extended this foundation-first approach into mechanistic interpretability work and applied research at Secondmind and Wayve, focusing on active learning, time-series modelling, feasible set estimation, and diffusion models for regression. He’s pioneered methods that combine diffusion processes with LLM knowledge and developed latent-space core-set selection techniques for expensive engineering simulations. Comfortable moving between theory and engineering, he also has experience in teaching and community-driven projects (Recurse Center) that reflect a broad, systems-level curiosity. Based in London, he blends rigorous academic insight with product-focused research to make AI systems more predictable and deployable.
9 years of coding experience
1 year of employment as a software developer
BlueDot Impact Governance Course, BlueDot Impact Governance Course at AI Safety FundamentalsB.A. (Hons) M.A. Master of Science - MSci Physics, B.A. (Hons) M.A. Master of Science - MSci Physics at University of CambridgeUniversity College London
English, Spanish, Chinese
Github Skills (43)
linux10
chromeos10
unix9
hyper-v9
uefi9
usb9
persistence9
prebuild9
bayesian-methods8
conversations8
bsd8
multiboot8
windows8
crowd8
wmi8
Programming languages (5)
Github contributions (5)
biggs/dotfiles
Mar 2017 - May 2022
Contributions:192 commits, 107 pushes, 1 branch in 5 years 3 months
biggs/tensor-trickle
Feb 2019 - Mar 2019
Contributions:17 commits, 12 pushes, 1 branch in 21 days
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