Title: Information Extraction Crossing Language, Robustness and Domain Barriers Speaker: Imed Zitouni (Microsoft) Time: 4:15pm-5:30pm, Thursday, April 25 Place: CUNY Graduate Center, rm 9204/9205, Abstract: Modern communication technologies have made massive amounts of real-time news information in several languages readily available. This led to the need to develop news-monitoring system that allows users to monitor multilingual news media in near real-time and search over stored content. In this talk I will briefly describe the architecture of a news-monitoring system and focus on its information extraction component. Information extraction is a crucial step toward understanding a text, as it identifies the important conceptual objects and relations between them in a discourse. I will address the portability of the used approach to different languages and show a method of propagating information into low resource languages from richer ones. Compared to other approaches that focus on clean-text, I will also show the robustness of our technique to less-well-formed input. For example, information extraction in a multilingual broadcast processing system has to deal with inaccurate automatic transcription and translation. The resulting presence of non-target-language text in this case yields many false alarms, which raise the research problem of making information extraction robust to such noisy input text. Biography Imed Zitouni is a Principal Researcher at Microsoft since September 2013 working on Relevance and Measurement techniques to improve Bing's search quality. Imed's current research interest includes information retrieval with focus on the use of statistics and machine learning techniques to develop web scale offline and online metrics for search engines. Imed is also interested in using Natural Language Processing (NLP) technologies to add a layer of semantics and understanding to search engines, with a belief that next generation search engines will be based on dialog and language understanding. Prior to joining Microsoft, Imed was a senior scientist at the Multilingual NLP group of IBM for almost a decade, where he served as team-lead in several NLP projects. Imed was key member of several government projects including the GALE program. Prior to IBM, he was a research member of Bell Laboratories, Lucent Technologies, for almost half dozen years working on language modeling, speech recognition, spoken dialog systems and speech understanding. Imed received his M.Sc. and Ph.D. with the highest-honors from the University-of-Nancy1 France. Imed is a senior member of IEEE, served as a member of the IEEE Speech and Language Processing Technical Committee (99-11), the Information Officer of the ACL SIG on Semitic-Languages, associate editor of TALIP ACM journal and a member of ISCA and ACL. He also served as chair and reviewing-committee-member of several conferences and journals. He is the author/co-author of more than 80 papers in international conferences and journals. His recent book is "Multilingual Natural Language Processing Application: from Theory to Practice", by Prentice Hall.