Maryam Zamanialaei is a geospatial data scientist specializing in wildfire risk analysis, remote sensing, and machine learning. At the University of California, Berkeley, she led work on Wildland-Urban Interface (WUI) fire modeling and mitigation, integrating Earth observation, fire spread models, and machine learning to quantify risk under varying weather and fuel scenarios. Her work integrates large-scale spatial analytics, ensemble fire simulations, and model interpretability to support decision-making for at-risk communities. She holds a Ph.D. and has authored technical reports and presentations on WUI risk, mitigation portfolios, and data-driven wildfire resilience.