Minho Kim
I am a postdoctoral scholar in the Stanford Urban Resilience Initiative, advised by Professor Jack Baker.
My research combines computational modeling and geospatial data science to model natural hazard risk, which inform build decision support tools that guide more proactive, risk-informed approaches. During my PhD, I focused on wildfires and used fire spread simulations, remote sensing, and network science within a
I received my PhD in Environmental Planning at UC Berkeley advised by Professors Marta C. Gonzalez and John Radke as a member of the HumNet Lab.
I received my BS and MS degrees in Civil and Environmental Engineering at Seoul National University, where I was advised by Professor Yongil Kim as a member of the SPINS Lab.
In our modern era of climate extremes, how can we map, model, and predict natural hazards to manage the risk on humans, infrastructure, and environment towards building a more sustainable and resilient future ?
Computational Modeling
Fire spread simulations on wildfire propagation, spatial networks of potential fire spread, and machine learning models that measure and characterize wildfire risk.
Geospatial Data Science
Spatial analysis using statistical and ML/DL methods to map and extract key insights from large-scale, multi-source remote sensing/GIS data.
Decision Support
A systems-based approach that integrates data-driven approaches with computational models into actionable tools for risk management and decision-making.