Mr. Ahmed Kamel

A Data Analyst and PhD applicant with a strong academic background in Data Science, Computer Applications, and Business Administration. He holds an MSc in Data Science from the University of Aberdeen, where his thesis examined the impact of sanitation infrastructure on elderly health using advanced statistical and machine learning methods. His research interests span public health analytics, infrastructure data, and predictive modelling. Professionally, he has worked with Camden Council in London, leading data migration, commercial property analytics, and cloud-based system implementation. He is proficient in Python, SQL, and Power BI, with a proven ability to translate complex datasets into actionable insights.

Research Interest: 

I am passionate about applying advanced data science techniques to address real-world public health and infrastructure challenges. My research explores how sanitation systems, environmental conditions, and urban planning impact the health and quality of life of ageing populations. I integrate statistical modelling, machine learning, and geospatial analysis to uncover hidden patterns in large datasets, providing evidence-based insights for policymakers and urban planners. My work bridges the gap between academic research and practical solutions, with a focus on improving health equity in rapidly urbanising regions.