Research / AI Foundations & Systems
AI Foundations & Systems
Overview
Advances core AI by strengthening algorithms and visual intelligence, while building smart data layers for retrieval-augmented generation (RAG) systems.
Research groups
AI & Data Discovery
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AI Foundational Optimizations
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Fanar GenAI Platform
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Team
Tools
Fanar
Fanar is an Arabic AI Large Language Model developed by the Qatar Computing Research Institute at Hamad Bin Khalifa University, a member of Qatar Foundation for Education, Science, and Community Development. It is sponsored by the Qatari government through the Ministry of Communications and Information Technology. Fanar bridges Arabic language and culture with the latest advancements in AI, aligning with Qatar National Vision 2030 and the objectives of the Digital Agenda 2030.
Fanar GenAI Platform
Related publications
AI Foundational Optimizations2026
Which Geometry Governs Few-Step Degradation in Latent Flow Matching?
Mohamed Aziz Khadraoui, Abdelkader Baggag — NeurIPS 2026 - BeNTo Workshop (2026)
AI Foundational Optimizations2026
Rapid disaster damage assessment using deep adversarial sliced Wasserstein domain adaptation
Fatma AlNaimi, Abdulaziz Al-Homaid, Ferda Ofli, Abdelkader Baggag — Neural Computing and Applications (2026)
AI Foundational Optimizations2026
Particles Don’t Care About Z: Towards Scaling Entropy Estimation of Unnormalized Densities
Safa Messaoud, Skander Charni, Elaa Bouazza, Ali Pourghasemi, Halima Bensmail — ICML (2026)
AI Foundational Optimizations2026
ISilDR: Isometric Seriation-based Dimensionality Reduction for Visual Cluster Analysis
Rene Cutura, Sophie Sadler, Quynh Quang Ngo, Michaël Aupetit, Michael Sedlmair — IEEE Transactions on Visualization and Computer Graphics (2026)
Fanar GenAI Platform2026
FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language Models
Masoomali Fatehkia, Enes Altinisik, Husrev Taha Sencar — EACL (2026)
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