Dan Klein

Dan Klein is a Professor of Computer Science at the University of California, Berkeley, specializing in natural language processing (NLP). His research interests encompass a broad range of topics within NLP, including parsing, machine translation, semantic representation, and computational linguistics. He is known for his work on probabilistic context-free grammars (PCFGs), tree adjoining grammars (TAGs), and discriminative parsing models.

Klein received his Ph.D. in Computer Science from Stanford University and has received numerous awards and honors for his research, including a Sloan Research Fellowship and a Presidential Early Career Award for Scientists and Engineers (PECASE). He is also recognized for his contributions to NLP education, having developed and taught popular NLP courses at Berkeley. Klein has also been involved in the development of open-source NLP tools and resources widely used in the research community. He has published extensively in leading NLP conferences and journals, and his work has significantly influenced the field. His research aims to develop robust and efficient NLP systems that can understand and generate human language.