Time: 2pm-3pm, Friday, Nov. 12 Place: Room 4102, CUNY Graduate Center, 365 Fifth Ave (34str&35str). Speaker: Dr. Dan Bikel (Google) Title: Language Technology Research at Google Abstract: Google's mission is to organize the world's information and make it accessible. While this mission statement is somewhat vague, it certainly includes understanding the information on the web and being able to present that information in coherent and succinct ways to users. In this talk, I will give an overview of the various kinds of language processing technology research that is going on at Google, including (but not limited to): machine translation, speech recognition, large-scale language modeling and sentiment analysis. I will also discuss my current primary research project, which is the improvement of speech recognition on YouTube videos. Bio: Dan Bikel graduated with honors from Harvard in 1993 with a degree in Classics, after which he spent a year as a graduate student at Harvard studying engineering, computer science and music. In 1994, he joined the Speech and Language Processing group at BBN in Cambridge,Massachusetts, where he co-created the first state-of-the-art namedentity finder, Nymble (now known as IdentiFinder(tm)). After spending three years at BBN, he became a Ph.D. student at the University of Pennsylvania's Computer and Information Science department, studying under Prof. Mitchell P. Marcus. At Penn, he built the first extensible syntactic parsing engine, discovering new and surprising properties of syntactic parsing models. Dan spent five years as a Research Staff Member at the IBM T. J. Watson Research Center, where he investigated many aspects of information extraction, including named entity coreference, semantic role labeling, quotation attribution detection, event and topic matching, oblivious computation for NLP applications and NLP system architectures. Dan is currently a Research Scientist at Google Research NYC, exploring ways to improve the quality and robustness of speech recognition, statistical parsing and question answering systems.