I work at the intersection of data science, artificial intelligence, and global health, with a research programme focused on developing and applying data-driven methods to address real-world public health challenges. My work is about methodological development and applied research, with a particular emphasis on AI-based approaches, including computer vision, to automate and improve data extraction in field and clinical research settings.
Affiliations
Centres
Teaching
Statistics for Health Data Science
Machine Learning: Deep Learning and Computer Vision
Research
I focus on the development of mathematically and statistically AI methods for public health and clinical applications, with particular highlights on computer vision, automated data extraction, and decision-support systems. A central theme of my work is the application of these methods in resource-constrained and field-based settings. I am especially interested in image-based diagnostics, monitoring and evaluation of health interventions, and the integration of heterogeneous data sources to support evidence-informed policy and public health practice.
Selected Publications
