I'm a data scientist / machine learning engineer with a background in computational / quantum physics. I write loads of python and typescript, and a little bit of everything else.
I like working on hard R&D problems involving computer vision, natural language processing, graph theory, representation learning, recommendation systems, and information retrieval.
I love turning those research projects into services which help people in the real world.
Developing ML-infused algorithms and experimental APIs for search, exploration, and discovery of stuff on wellcomecollection.org.
Distilled huge datasets to understand visitors' motivations, expectations, and needs when visiting the museum online and IRL.
Built a matching/recommendation system for an app with hundreds of thousands of users around the world.
MSci Physics, 2:1
Thesis: Correlations between water fragments on silicon
I try to share what I've learned through blog posts, reusable code, and/or talks at conferences and universities.
I've advised, mentored, and supervised first-time conference speakers, artists, researchers in industry and academia, grant funding applicants, and students all the way from GCSE to PhD.
I care a lot about the ethical implications of my work. I'm a member of Mozilla's Building Trustworthy AI working group and the Museums + AI Network.
I've built a lot of open source tools, sites, and services outside of work to sharpen my own development skills and experiment with new technologies.
I like swimming outdoors, especially through the winter. I've been cycling in London for eight years and I've only been hit by four cabs.