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

Team

Tools

Fanar

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 Foundations and systems2026

PAM: Training Moderation Filters from Policy-Derived Supervision

Masoomali Fatehkia, Enes Altinisik, Mohamed Osman, Husrev Taha Sencar — Third Conference on Language Modeling (COLM) (2026)
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AI Foundations and systems2026

The Numerical Linear Algebra of Large Language Models

Abdelkader Baggag, Yousef Saad — arXiv (cs.LG; cross-listed in math.NA) (2026)
DOI
AI Foundational Optimizations2026

Which Geometry Governs Few-Step Degradation in Latent Flow Matching?

Mohamed Aziz Khadraoui, Abdelkader Baggag — NeurIPS 2026 - BeNTo Workshop (2026)
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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)
DOI
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)
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