Biology from the bottom up
Initial thoughts on transforming bioengineering into software engineering.
AI
TableDiffusion
A deep learning algorithm I developed for training diffusion models on tabular data under differential privacy guarantees.
FOMO: LLM embeddings to keep up with AI
An open source newsreader app I built using LLM embeddings to semantically prioritise arXiv and Github updates.
Yesterday's cutting edge is today's table stakes
The past 18 months in AI have been a whirlwind-clusterfuck of acceleration, innovation, and chaos.
Building PorePatrol LLM at the Anthropic Hackathon
We used LLaVA and Claude to build a crazy multimodal LLM health assistant. OpenAI made it redundant the next week.
Optimising cost, quality, latency
There is a trifecta of variables that just about everyone building generative AI systems cares about — cost, quality, and latency. As is often the case in computing, there is a trade-off between these properties. And all three are bought with the currency of performance.
Learning quant. trading with ML on Numerai
Making 95% annual return on the hardest data science tournament in the world, for fun and profit.
Generative models for synthesising private datasets
My MSc thesis and what it aims to do for biomedical science.
Quantified Sleep
This project applied statistical learning techniques to an observational Quantified-Self (QS) study to build a descriptive model of sleep quality. A total of 472 days of my sleep data was collected with an Oura ring. This was combined with a variety of lifestyle, environmental, and psychological data, harvested from multiple sensors and manual logs.