معرفی
Helen Yannakoudakis is a Senior Lecturer in Natural Language Processing at King's College London's Department of Informatics, affiliated with the University of Cambridge's NLIP Group. She holds a PhD from the University of Cambridge and has served as a Turing Fellow and Fellow of the Higher Education Academy. Her research focuses on machine learning for NLP, including few-shot learning, meta-learning, and societal applications like hate speech detection and educational tools. She has won the NeurIPS 2020 Hateful Memes Challenge and led the development of Write&Improve, an automated writing assessment system.
Education: PhD in Natural Language Processing (University of Cambridge), MPhil in Computer Speech, Text & Internet Technology (Cambridge), BSc in Computer Science (Athens University of Economics & Business).
Research Interests: Few-shot learning, multilingual NLP, abusive language detection, mental health detection, and automated language teaching. Her work bridges machine learning and education, with applications in bias mitigation and ethics in AI.
Publications: Over 20 peer-reviewed papers in top venues (ACL, NeurIPS, EMNLP) covering topics like GEC, hate speech detection, and meta-learning frameworks. Recent work includes prompting LMs for language education and commonsense-enhanced transformers for comprehension.
Awards & Roles: Area Chair for ACL 2025/NeurIPS 2024, co-founder of Kinhub (AI education tools), and contributor to the English Profile Programme. Her research emphasizes ethical AI and real-world societal impact.
