KEYNOTE SPEAKERS

Biography

Firas Ben Hassan is the Head of Agentic AI Solutions Hub at Allianz Technology in Munich, where he leads the enterprise-wide strategy and deployment of advanced AI systems, including Generative and Agentic AI solutions. He manages a global team of AI experts delivering high-impact products with significant business value. He previously served as Head of Artificial Intelligence Services at Allianz and has extensive experience in data science, machine learning, and AI-driven transformation across insurance and enterprise domains. Firas is also an AI Guest Lecturer in many universities worldwide and has delivered talks at major international conferences across the US, Europe, and the Middle East. He is recognized as an AI Innovator of the Year (Stevie Awards 2025) and is actively contributing to shaping responsible and scalable AI adoption in industry.

Title and short abstract of the presentation: 

• From Generative AI to Agentic AI: Shaping the Next Frontier of Intelligent Systems

This keynote explores the evolution from Generative AI to Agentic AI, highlighting how AI is transitioning from passive content generation to autonomous, goal-driven systems capable of reasoning, planning, and acting.

The talk is designed to inspire and equip PhD students with:

• A clear understanding of the shift from LLM-based systems to multi-agent architectures

• Real-world applications of Agentic AI in enterprise environments

• Key research challenges and opportunities in building autonomous AI systems

• Practical insights on how to bridge academic research with industrial impact

The session will provide both a strategic vision of the future of AI and concrete examples to help students position their research in this rapidly evolving landscape. 

Biography

Houda Bouamor is an Associate Professor at Carnegie Mellon University in Qatar (CMU-Q). Her research focuses on Natural Language Processing for Arabic and its dialects, with particular interest in low-resource and underrepresented language varieties. Her work spans dialectal Arabic processing, automatic Arabic essay scoring, and the development of assistive NLP technologies for users with dyslexia. Through these directions, she is committed to advancing inclusive NLP that serves both underrepresented languages and underserved users. She has published extensively in top-tier NLP venues and has been actively involved in the Arabic NLP research community through organizing workshops, shared tasks, and conferences.

Title and short abstract of the presentation: 

• Inclusive Arabic NLP: Bridging Gaps in Dialectal Processing, Automatic Essay Scoring, and Assistive Technologies for Dyslexia

Despite the rapid progress of large language models, significant gaps remain in how Natural Language Processing serves linguistically diverse communities and users with specific needs. Arabic, with its rich variety of dialects and its millions of speakers, continues to pose unique challenges: most tools and resources are tailored to Modern Standard Arabic, leaving dialectal varieties underrepresented and, in many cases, underserved. At the same time, applied domains such as automated educational assessment and assistive technologies highlight the gap between what NLP can technically do and what it actually delivers to real users.

In this talk, I will present recent work on advancing inclusive NLP for Arabic through three connected directions. First, I will discuss progress and open challenges in dialectal Arabic processing, from resource creation to modeling. Second, I will present our work on Automatic Arabic Essay Scoring, where NLP meets education in a low-resource setting. Third, I will share insights from developing NLP-based assistive technologies for users with dyslexia, where language technology becomes a tool for accessibility. Together, these directions illustrate a broader vision: NLP that bridges gaps not only between languages, but also between technology and the people it is meant to serve.