I am a geospatial researcher passionate about advancing the use of GeoAI to improve disaster resilience, urban and transportation infrastructure, and public health outcomes and equity. I have a background in Surveying Technology (BT, 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 while working on strengthening my skills in Python for geospatial workflows and spatial statistics, and preparing to pursue graduate research on GeoAI and Disaster Resilience. My long-term goal is to bridge cutting-edge geospatial technologies in addressing pressing disaster resilience challenges.

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 needs, while also preparing for a PhD that will allow me to expand into predictive modeling and advanced GeoAI for global disaster resilience.

I see my research journey as a bridge:

Master’s → building solid expertise in GIS and Remote Sensing, GeoAI applications and Disaster Resilience.

PhD → advancing toward predictive modeling, social sensing in disaster 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 Formula 1 (Tifosi Ferrari), hiking, cultural music/dances, karaoke, nature photography, WWE, influencer boxing, a little bit of Hockey, and a strong Gunner (Arsenal FC).

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