Sebastian Ruder is a researcher in natural language processing (NLP) and machine learning, with a particular focus on transfer learning and multilingualism.
During his studies, Ruder was a research intern at Google, where he worked on improving language models for speech recognition.
After completing his master’s degree, Ruder joined the NLP group at the University of Edinburgh as a PhD student, where he focused on transfer learning for NLP tasks. His research explored how pretraining language models on large amounts of unlabeled data can improve their performance on downstream NLP tasks. He also studied how to transfer knowledge across different languages to improve NLP models in low-resource languages.
In addition to his academic work, Ruder has contributed to the development of several widely used NLP resources and datasets. He is currently a research scientist at Google, where he continues to work on developing and improving NLP models.
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