Artificial Intelligence for Disaster Management:
Building Damage Identification and Flood Event Detection Using Deep Learning
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Overview
The increasing frequency and severity of natural disasters present critical challenges to global security. Traditional disaster assessment methods are often slow and resource-intensive, delaying vital response efforts. This Advanced Study Institute (ASI) is a high-level, intensive tutorial course designed to address these challenges by leveraging the transformative power of Artificial Intelligence and Deep Learning. Over nine days, participants will gain the skills to develop and deploy automated systems for rapid and accurate disaster impact assessment, focusing on building damage and flood detection from satellite and aerial imagery.
Dates: November 17 – 23, 2025 (7 Days)
Location: Institute for Simulation and Training (IST), University of Central Florida, Orlando, FL, USA
Format: Hybrid (In-person or online)
Co-Directors:
Dr. Bulent Soykan (NATO country Project Director, University of Central Florida, USA)
Distinguished Professor Saeid Nahavandi (Partner country Project Director, Swinburne University of Technology, Australia)
Co-PIs:
Dr. Ghaith Rabadi (Director and Professor, University of Central Florida, USA)
Dr. Soheil Sabri (Assistant Professor, University of Central Florida, USA)
Event Objectives
Develop practical skills in building, training, and deploying deep learning models.
Master end-to-end workflows from data collection to operational deployment.
Apply advanced techniques using real-world datasets (CNNs, transfer learning).
Integrate AI solutions into existing disaster management frameworks.
Establish a professional network for future international collaboration.
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