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Ghadi Babour

After KAUST Academy

Ghadi works at Lucidya and was promoted there in April 2026. Ghadi earned two NVIDIA generative AI certifications in July 2025, and attended KAUST Academy's summer AI program at the University of Oxford in 2024.

Summer projects

Artificial Intelligence Specialization · Cohort 2024

Accelerated Post-Disaster Recovery: An AI-Powered System for Damage Assessment and Reconstruction Prioritization

This project introduces an innovative AI-driven framework to revolutionize post-disaster recovery efforts. Leveraging UAV imagery and advanced AI techniques, our system rapidly assesses damage to buildings and infrastructure using an Attention U-Net model for image segmentation. Unsupervised learning then clusters affected areas based on damage severity, building importance, and distance, utilizing both segmentation results and Google Maps metadata. A reinforcement learning model, employing PPO and DQN algorithms, optimizes resource allocation and prioritizes reconstruction efforts, aiming to minimize total recovery time. This integrated approach promises faster, more accurate damage assessment and data-driven decision-making, significantly reducing the time needed to restore affected communities and setting a new standard for efficient disaster response strategies.

See it in the program report (PDF)

Artificial Intelligence Specialization · Cohort 2023

Multimodal Approach: For Palm Diagnosis and Red Weevil Early Detection

The project is about developing a system that can identify and diagnose palm trees that are infested by red palm weevils, a species of pests that causes serious damage to palm trees worldwide. The system uses a deep multimodal approach that combines audio and image data to detect infestation in early stages and provide accurate treatment recommendations. The project aims to protect palm trees from red palm weevils and reduce their economical and environmental impact.

See it in the program report (PDF)

Artificial Intelligence Specialization · Cohort 2023

Yaqeen: Deep Learning-Based System for Unbiased Recruitment

Yageen is an AI-powered recruitment system that helps employers find the best employees, regardless of their background, gender, race, or other factors. Yageen addresses the problem of bias and discrimination in the hiring process, which can lead to missed opportunities, lower diversity, and legal risks. Yageen targets the HR and recruitment industry, as well as any organization that wants to improve their hiring practices and outcomes.

See it in the program report (PDF)

With KAUST Academy

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