I am a researcher in mathematical physics + machine learning, currently in the final year of my DPhil at the University of Oxford. In April 2025, I will be starting a fellowship at Anthropic. If you’re wondering why, I recommend reading Anthropic’s core views on AI safety: I find they align with my own.
I like applying new tools from ML and data science to mathematical settings. Examples include long time-horizon reinforcement learning, discrete diffusion modelling for pathfinding in abstract rewriting systems/Cayley graphs, or evolutionary search using large language models. I also work on using neural networks* to solve partial differential equations on topologically nontrivial (typically Calabi-Yau/G₂) manifolds. We used these to calculate the first set of quark masses in heterotic string theory**. For more, see my github and inspire HEP. I am interested in the geometry of special holonomy manifolds, including connections to optimal transport.
* These seem to be known as PINNs.
** Caveats: first set of physical Yukawa couplings in heterotic string theory in nonstandard embedding. Otherwise, this is tree-level, compactification-scale.
contact
- email: threeletterfirstname lastnamenohyphen at \*mail dot com
- github
Projects
- Diffusion models on Cayley graphs - repo
- Genetic programming with LLMs for mathematical discovery - (paper) (repo)
- Calculating Yukawa couplings from heterotic compactifications using machine learning - repo
- Alpha' corrections to Calabi-Yau metrics using machine learning - repo
Knot unknotting using the Möbius functional
(1,3) torus (un)knot
Random unknot
The Möbius energy functional is defined on embeddings of S¹ into R³; it is conjectured to have a unique critical point in the space of S¹-embeddings ambient isotopic to the round unknot. If that were true, it would define an algorithm for unknotting any unknot, however complicated! One application of the code written for this animation was studying possible counterexamples to this conjecture.