Daniel M. Bikel (email@example.com) is a Research Scientist at Google Research. He graduated with honors from Harvard in 1993 with a degree in Classics–Ancient Greek and Latin. From 1994 to 1997, he worked at BBN Technologies on several natural language processing (NLP) problems, including development of the first high-accuracy, machine learning–based name-finder. He received M.S. and Ph.D. degrees in computer science from the University of Pennsylvania, in 2000 and 2004, respectively, discovering new properties of statistical parsing algorithms. From 2004 through 2010, he was a Research Staff Member at IBM Research, working on wide variety of NLP problems, including parsing, semantic role labeling, information extraction, machine translation and question answering. From 2010 to May, 2015, Dr. Bikel worked on NLP and speech processing research at Google. As a researcher there, he built dynamic adaptation of language models for automatic YouTube captioning, built a generic framework for reranking and was a founding member of the team that built the semantic parser that lay behind Google Now (which has since become the Google Assistant). From 2015-2017, Dr. Bikel was Principal NLP Scientist & Senior Manager at LinkedIn. In that role, he built and led a team of NLP researchers and engineers, building text processing methods for use throughout the company, including deep learning approaches specific to LinkedIn’s problem areas. In September of 2017, Dr. Bikel re-joined Google, continuing to work on natural language processing problems, leading a research team focused on using NLP and machine learning to understand specialized domains. He has published numerous peer-reviewed papers in the leading NLP conference proceedings and journals, and has built software tools that have seen widespread use in the NLP community. He co-edited the book “Multilingual Natural Language Processing Applications: From Theory to Practice”, published by IBM Press/Pearson in 2012.