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Hello! I am currently a PhD student @ImperialCollege. My research lies at the intersection of machine learning, physics, and differential geometry. The goal of this research is to leverage reduced-order models for high-dimensional, complex physical phenomena - utilising tools from differential geometry and physics to operate directly on low-dimensional manifolds.

Previously, I worked as a machine learning research intern @NasaJPL, @ESA, @MindFoundry, @Dyson, and @BAESystems.

Daniel Kelshaw's Projects

bolt icon bolt

Lattice Boltzmann Simulator

fds icon fds

Flight Dynamics Simulator

gpybo icon gpybo

Gaussian Processes | Bayesian Optimisation

ml_collections icon ml_collections

ML Collections is a library of Python Collections designed for ML use cases.

pyga icon pyga

Python Genetic Algorithms

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PyTorch implementation of 'Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning'

riot icon riot

An actor-model multi-core scheduler for OCaml 5 🐫

torchnalu icon torchnalu

PyTorch implementation of 'Neural Arithmetic Logic Units'

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