Temidayo Popoola

Temidayo Popoola is a Doctoral researcher at Texas Tech University whose research focuses on flood hazards, housing damage, community vulnerability, and climate-related extreme events. His work combines geospatial analysis, interpretable machine learning, and climate data analytics to improve flood risk assessment and support more resilient communities.

Popoola’s research examines how exposure, vulnerability, and hazard intensity interact to shape flood-related housing losses across U.S. flood events and regions. His current work integrates National Flood Insurance Program claims data, exposure and vulnerability indicators, and downscaled climate projections to model both historical and future residential flood damage at the census-tract level. His broader research goal is to improve decision-making for disaster risk reduction, resilience planning, and climate adaptation.

Before joining Texas Tech University, he worked extensively in meteorology, operational forecasting, climate science, and research training across West Africa. He served with the Nigerian Meteorological Agency and contributed to the Global Challenges Research Fund African Science for Weather Information and Forecasting Techniques Project, supporting the translation of high-impact weather forecasting, satellite remote sensing, and climate research into operational practice.

Popoola is a Bill Anderson Fund Fellow and a Department of Housing and Urban Development Research Center of Excellence in Capacity-building for Resilient Housing Fellow. His technical expertise includes Python, machine learning, ArcGIS, Google Earth Engine, and climate data analysis.