Martin Burke PhD
Quantitative Researcher | AI, Model Validation & Computational Science | PhD, Imperial College London
Martin Burke is a quantitative researcher working at the intersection of AI and quantitative finance. Currently researching AI-safety debate frameworks for the UK AI Safety Institute — with broader interests across mechanistic interpretability and applied AI — he previously spent a decade validating derivatives and counterparty-credit-risk models at banks including Citi. He holds a PhD in Theoretical Chemistry from Imperial College London, where he pioneered the application of sum-of-squares optimisation — a technique from real algebraic geometry — to molecular energy minimisation.
Now focused on AI — building practical AI applications, with a particular interest in AI safety and mechanistic interpretability.
- AI research (safety, mechanistic interpretability, applied AI / software development)
- Quantitative finance (model validation, derivatives)
- Computational / theoretical chemistry