Bridging Medicine, Data Science & Discovery
MBBS
MSc Clinical & Molecular Microbiology
MSc Drug Discovery & Development
I am a medical doctor, MBBS, MSc Clinical & Molecular Microbiology, MSc Drug Discovery & Development. My work bridges biomedical research, infectious diseases, and data science, with a particular focus on antimicrobial resistance, immuno-oncology, and AI-driven healthcare.
I am building a portfolio at the intersection of medicine, machine learning, and translational research — from systematic reviews and meta-analyses to bioinformatics pipelines and predictive modelling.
Selected bioinformatics, data science, and pharmaceutical research projects (code + outputs).
Exploratory data analysis and visualisation of nanostructured lipid carrier (NLC) formulation datasets (particle size, PDI, zeta potential, encapsulation efficiency), with publication-ready plots.
A reproducible pipeline that converts ECG images into digital time-series signals for downstream analysis, including preprocessing, extraction steps, and visual validation.
A compact bioinformatics project mapping key virulence factors and mechanisms in Helicobacter pylori, linking genes, pathways, and clinical relevance in a structured, visual format.
A collection of short, practical data projects built from thesis datasets: cleaning, plotting, interpretation, and presentation-ready reporting for formulation science.
Data-driven analysis of nanostructured lipid carrier (NLC) formulation datasets, exploring relationships between particle size, PDI, zeta potential, and encapsulation efficiency using Python-based statistics and modelling.
Personal academic portfolio showcasing research, data projects, and outputs. Built with HTML/CSS/JS and deployed via GitHub Pages.
Reproducible statistical analysis of particle size distributions of meropenem-loaded nanostructured lipid carriers (NLCs), including thyme oil-modified formulations. Analysis performed in R with automated normality testing, group comparison, and publication-ready figure generation.
Presentations, tutorials, research clips, and more.
If you would like to collaborate on research, data science projects, or academic writing, feel free to get in touch.