Biography
Dr. Ahmed Hassan is a leading researcher in neural-symbolic AI and natural language processing, with a focus on Arabic language understanding. He directs the AI Research Lab at AUC and has published extensively on hybrid AI architectures that combine deep learning with symbolic reasoning. His work on ethical AI frameworks for Middle Eastern contexts has been adopted by multiple regional institutions.
Research Projects
Neural-Symbolic Reasoning for Arabic NLP
ActiveDeveloping hybrid AI systems that combine deep learning with symbolic reasoning to improve natural language understanding for Arabic text and speech.
AI Ethics and Value Alignment
ActiveResearching methods to ensure AI systems align with human values and cultural norms, with focus on Middle Eastern and North African contexts.
Cognitive Architecture for Multi-Agent Systems
CompletedDesigned computational models of human cognition to enable multiple AI agents to collaborate and coordinate effectively in complex environments.
Selected Publications
Neural-Symbolic Integration for Arabic Dialect Understanding
Multi-Agent Cognitive Architectures for Collaborative Problem Solving
Ethical AI Frameworks for Middle Eastern Contexts
Transfer Learning Across Arabic Language Variants
Common Sense Reasoning in Neural-Symbolic Systems
Expertise
Education
PhD in Computer Science
Stanford University
2018
MSc in Artificial Intelligence
MIT
2014
BSc in Computer Engineering
Cairo University
2012
Awards & Honors
- Best Paper Award, ACL 2023
- Young Researcher Award, Egyptian Academy of Sciences, 2022
- Outstanding PhD Thesis Award, Stanford University, 2018