ALAN AKBIK

I am professor of machine learning at Humboldt-Universität zu Berlin. My research focuses on natural language processing (NLP), i.e. methods that enable machines to understand human language. This spans research topics such as transfer learning, few-shot learning and semantic parsing, as well as application areas in large-scale text analytics. My research is operationalized in form of the open source NLP framework Flair that allows anyone to use state-of-the-art NLP methods in their research or applications. Together with my group and the open source community, we maintain and develop the Flair framework... Universal Proposition Banks. In this line of research, I am investigating methods for semantically parsing text data in a wide range of languages, such as Arabic, Chinese, German, Hindi, Russian and many others. In order to train such parsers, we are automatically generating Proposition Bank-style resources from parallel corpora. We are making all resources publicly available, so..