Role & Position
I am a mathematically-oriented Data Scientist currently applying myself to a diverse range of problems available to me at Mott MacDonald, working on large datasets and directly with clients.
I tend to be most interested in mathematical and statistical problem solving where it can be applied to problems in scientific and engineering domains to maximise positive social outcomes. I thoroughly enjoy researching and developing novel solutions to problems in technical fields.
Feel free to get in touch at email@example.com or read my curriculum vitae.
Projects & Research
Raytrace Rendering using Python and a healthy amount of Linear Algebra
This project aims to build a simple rendering pipeline for educational purposes. It's not the fastest renderer in the world and has no hardware acceleration, but good fun to design, build and play with.
Teaching Vector Properties using Time Dependant Particle Simulation
This project looks at extending the idea of visualising divergence and curl by imagining the vector field as a fluid like object. The way I approach this is to look at a particle simulation where the particles are spawned with a velocity that pertains to the value of the vector field at that point.
Preprocessing Text Data for Machine Learning with a Neural Network
Looking into taking data from public sources, and turning it into a resource with greater machine learning value using Python and Pandas. Using One Hot Encoding and considering different simplifications of the dataset for optimal learnability without losing too much entropy.