— First comprehensive Lebanese Building Footprints map generated autonomously using deep learning
— Building type classification and damage assessment using very high-resolution satellite imagery
— Sci-Net: a scale-invariant model for building detection from aerial images
— Solar Potential Map for Lebanon based on multi-class building segmentation
— Lebanese Road Crashes Platform (LRCP)
— WAVE1609 Tool: modeling and simulation of WAVE 1609.4-based multi-channel VANETs
Selected publications:
— 'Influence of Snow Cover on Water Capacity in the Qaraaoun Reservoir, Lebanon' (2021, Arabian Journal of Geosciences)
— 'Analyzing factors associated with fatal road crashes: A machine learning approach' (2020, International Journal of Environmental Research and Public Health)
Background
Associate Researcher at the Lebanese National Center for Remote Sensing (CNRS)
Founded the GEOspatial Artificial Intelligence (GEOAI) research group
Research focuses on AI-assisted mapping across urban analytics, transportation, waterbody monitoring, and crop-yield estimation
Develops deep learning-based tools for automated urban feature extraction and multi-source crowdsourced data integration
His models and data analyses support humanitarian response and inform urban policy for social good
Previously contributed to Intelligent Transportation Systems (ITS), vehicular cognitive networks, and the IEEE P1609 standard Working Group