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Danah Almuhaysin

After KAUST Academy

Danah works as a NOC Engineer at Capgemini Engineering, joined in February 2026 on the aramco digital 450 MHz project. Danah presented a paper on AI fainting detection at the Great Mosque of Mecca at IEEE ICMI 2026 and graduated from the Saudi Digital Academy cloud and DevOps bootcamp in December 2025.

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

Solving Dialect Bias in Deep Neural Networks for Arabic Speech Tasks

In a world where language plays an influential role in shaping our identities, distinguishing dialects within a language is vital. Accurate dialect identification allows language technologies to adapt to regional nuances. However, existing models have biases and limitations, hindering effectiveness. Our aim is to enhance fairness, robustness, and generalizability, enabling models to accommodate diverse linguistic characteristics in Arabic dialects.

See it in the program report (PDF)

With KAUST Academy

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