معرفی
Youmna Farag is a Research Fellow in the Department of Computer Science and Technology at the University of Cambridge. Her work focuses on Machine Learning and Natural Language Processing (NLP), with a particular emphasis on dialogue systems, discourse coherence, and adversarial NLP challenges. She is affiliated with the William Gates Building and contributes to interdisciplinary research in computational linguistics and AI applications.
Her research interests span neural approaches to discourse analysis, automated essay scoring, and the ethical implications of dialogue systems. Recent projects include developing Speech-LLM frameworks (e.g., WHISMA) for zero-shot spoken language understanding and feature-based models for dialogue constructiveness assessment.
Publications highlight her contributions to coherence modeling, multi-task learning, and adversarial robustness in NLP. She has also explored hardware-software integration in safety systems, such as an Arduino-based vehicle accident reduction system.
No academic awards or supervised students are explicitly mentioned in the provided materials. She is part of a vibrant research community at the University of Cambridge, collaborating on cutting-edge projects in AI and computational linguistics.
