Bashar Alhafni
Assistant Professor of Natural Language Processing
Research Interests
Professor Alhafni's research focuses on Arabic natural language processing (NLP), with a particular interest in building human-centered language technologies. He directs the Arabic AI Modeling (Aram) Lab, where his work spans a range of areas, including grammatical error detection and correction, dialectal Arabic text normalization, text simplification, readability assessment, machine translation, and controlled natural language generation. He is especially interested in developing Arabic NLP applications that support education in Arabic and contribute to social good.
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Prior to joining MBZUAI, Professor Alhafni earned his Ph.D. in Computer Science from New York University, where he was a member of the Computational Approaches to Modeling Language Lab at New York University Abu Dhabi. His doctoral research focused on controlled Arabic natural language generation with applications in AI for education and social impact. This included the development of models and systems for Arabic grammatical error correction, text normalization, and user-centric text rewriting. He also contributed to the development of open-source tools and language models that support Arabic NLP research. Professor Alhafni holds a Master of Science in Computer Science from the University of Southern California, where he conducted research at the Information Sciences Institute on low-resource machine translation and event-relation extraction. He also holds a Bachelor of Science in Computer Science from the University of Bridgeport. Beyond academia, he has conducted applied AI and NLP research at companies such as Grammarly and Dataminr, where he contributed to advancing personalized text generation, multilingual NLP, and extractive summarization technologies.
- Ph.D. in Computer Science from New York University
- Master of Science in Computer Science from the University of Southern California
- Bachelor of Science in Computer Science from the University of Bridgeport