Data Scientist specialising in bioinformatics, machine learning, and clinical data analytics. MSc Biomedical Engineering · Imperial College London.
About me
I'm a Bioinformatics-focused Data Scientist with a background in Biomedical Engineering. I build production-scale genomic analytics pipelines, deploy machine learning models for patient stratification, and translate complex molecular datasets into structured, decision-ready evidence.
I hold an MSc in Biomedical Engineering from Imperial College London and a First Class BEng from Queen Mary University of London. This site is where I write about the ideas and topics that shape how I think, from genomics to machine learning to medicine.
Multivariable calculus, linear algebra, and signal processing, the rigour behind every model I build.
Living systems are noisy, dynamic, and deeply interconnected, precisely what makes data science on them so compelling.
The Blog
Biology and engineering seem worlds apart, yet their intersection is where the most exciting science happens. Bioinformatics and data science give me the tools to make sense of complex biological systems: finding patterns in genomic data, modelling disease progression, and translating raw molecular information into something meaningful.
The human genome contains billions of base pairs. A single RNA-seq experiment generates millions of reads. A clinical dataset can span thousands of patients across years of follow-up. Making sense of that data, rigorously and reproducibly, is both a technical challenge and a creative one.
This blog is where I explore those ideas, from the logic of machine learning pipelines to the biology they're trying to decode. I hope you find something here that sparks your curiosity.
