I am a Health Data Scientist at Oxford Population Health and an MSc graduate from LSHTM. My work sits at the intersection of advanced AI, clinical operations, and public health surveillance.
🔭 Current & Recent Work
- SchistoTrack (Oxford Big Data Institute): Managing complex, multi-dimensional cohort data (Survey, Imaging, Spatio-temporal) to improve schistosomiasis treatment strategies in Uganda.
- Microsoft Premonition (MSc Thesis): Benchmarked CNNs (ResNet-50) vs Vision Transformers (Swin/ViT) for infectious disease vector classification to detect "shortcut learning" in AI models.
🔐 Code Availability & Data Governance As a researcher working with sensitive clinical data and industry partners, strict data governance is a priority.
- Microsoft Premonition: The source code and datasets for this project are kept privately for industry purposes to protect proprietary intellectual property (IP) and adhere to confidentiality agreements.
- Clinical Data: Repositories related to my work with certain companies remain private to comply with GDPR, GCP, and patient confidentiality standards.
🛠 Technical Stack
- Languages: Python (Pandas, NumPy), R (Tidyverse, ggplot2), SQL (used in projects)
- AI / Deep Learning: PyTorch, TensorFlow, Scikit-learn, Grad-CAM (Explainability)
- Tools: Git, Excel Macros, Bash, Veeva