Fiona Blackett is a PhD mathematician and intern researcher at VERSES AI, blending deep theoretical work in homotopy theory, cohesive topoi, and differential cohomology with applied machine learning grounded in physics principles and topological data analysis. Based in the Iowa City–Cedar Rapids area, she brings a decade of technical experience that spans mathematical physics, Calabi–Yau A∞ categories and Floer homology, and a background in information security. Fiona maintains an active interest in formal verification and the intersection of category theory with type theory, collaborating with the MSP group at the University of Strathclyde. Her profile reflects a rare hybrid of rigorous pure-math research and practical ML research, often surfacing in side projects and academic code shared via her website and GitHub.
10 years of coding experience
Doctor of Philosophy - PhD, Mathematics, Doctor of Philosophy - PhD, Mathematics at University of Strathclyde
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