Tolulope Oladeji
Geospatial Data Scientist
I am a doctoral researcher at the University of Cincinnati working at the intersection of Geospatial Data Science, Artificial Intelligence, and Environmental & Public Health. My work bridges spatial statistics, geographic information science, Spatial Epidemiology and GeoAI to understand how place, environment, and context shape human health, environmental and ecological outcomes.
My research focuses on developing advanced spatiotemporal and AI-driven approaches — including Bayesian hierarchical models, geospatial neural networks, and causal inference frameworks — to analyze environmental exposures and predict population-level health risks. I am particularly interested in geospatial AI and environmental health analytics, with applications in maternal and child health, environmental monitoring, and decision intelligence. Through this work, I aim to generate actionable, data-driven insights that inform public health interventions and policy across both high- and low-resource settings.
Beyond research, I am passionate about mentoring emerging Geospatial AI researchers and fostering open science communities in GeoML. I am actively involved with the Digital Epidemiology Laboratory and continuously seek opportunities to contribute to collaborative, mission-driven work with real-world impact. I am open to collaborating with organizations such as the CDC, municipal governments, NGA-affiliated research labs, and international partners to develop spatial decision-support systems.