I am a geospatial researcher passionate about advancing the role of GeoAI, spatial statistics, and healthcare GIS in addressing pressing societal challenges. I have a background in Land Surveying (BSc, 2023) and hands-on experience in GIS, cartography, topography, remote sensing, and geospatial programming with Python. I am currently preparing for my graduate school journey. My research vision is to integrate GeoAI-driven spatial analytics into healthcare, with the long-term goal of building tools and models that improve public health decision-making, disease surveillance, and spatial epidemiology both in Africa and globally.

Since graduation, I have dedicated my time to self-learning, volunteering, and advancing my technical foundation in Python, geospatial data science, spatial statistics, and intermediate machine learning workflows. I am deeply motivated to bridge the gap between cutting-edge spatial technologies and real-world healthcare needs, while also preparing for a PhD that will allow me to expand into predictive modeling and advanced GeoAI for global health resilience.

I see my research journey as a bridge:

Master’s → building solid expertise in spatial statistics, healthcare GIS, and GeoAI applications.

PhD → advancing toward predictive modeling, machine learning for health risk analysis, and global health resilience research.

My long-term vision is to become a Geospatial Data Scientist, working at the intersection of GeoAI, healthcare, and global resilience. I am always open to learning, collaboration, mentorship, and new research opportunities.

Apart from my academic and career endeavours, I am a social and outspoken individual. I enjoy hiking, cultural music/dances, karaoke, nature photography, WWE, influencer boxing, Formula 1 (Tifosi Ferrari), a little bit of Hockey, and a strong Gunner (Arsenal FC).

Explore my GitHub at https://github.com/Iamnyatichi.